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"\"GSSg9\"GSSg9/S.9GSGSSl\ "\"GS5\"GS|5\"GS5S9S59\ "GS\ "\"GSSg9\"GSSg9/S.9GSGSGSd\ "\"GS5\"GS5\"GS5S9S59\ "GSY\ "\"GSYSg9\"GSSg9/S.9GSYGSGSd\ "\"GSj5\"GS5\"GS5S9S59\ "GS4\ "\"GS4Sg9\"GSSg9/S.9GS4GSS1\ "\"GS5\"GS5\"GS5S9S59\ "GS\ "\"GSSg9\"GSSg9/S.9GSGSS1\ "\"GS|5\"GS5\"GS5S9S59\ "GS:\ "\"GS:Sg9\"GSSg9/S.9GS:GSS1\ "\"GS5\"GS5\"GS5S9S59\ "GS\ "\"GSSg9\"GSSg9/S.9GSGSS1\ "\"GS5\"GS5\"GS5S9S59\ "GS@\ "\"GS@Sg9\"GSSg9\"GSSg9\"GSSg9/S.9GS@GSS1\ "\"GS5\"GS5\"GS5S9S59\ "GSE\ "\"GSESg9\"GS?Sg9/S.9GSEGSSl\ "\"GS5\"GS5\"GS5S9S59\ "GSl\ "\"GSlSg9\"GSBSg9/S.9GSlGSSlGS\ "\"GS5\"GS5\"GS5S9SC9\ "GSn\ "\"GSnSg9\"GSCSg9/S.9GSnGSSlGS\ "\"GS5\"GS5\"GS5S9SC9/GS9Pr\\\GS'g(z?DO NOT EDIT THIS FILE DIRECTLY, INSTEAD RUN `make package-data`N)Decimal)*) providers anthropic Anthropiczhttps://api\.anthropic\.comz%https://www.anthropic.com/pricing#apiclaude)containsusage input_tokensT)pathdestrequiredcache_creation_input_tokensFcache_read_input_tokenscache_write_tokenscache_creationephemeral_5m_input_tokenscache_write_5m_tokensephemeral_1h_input_tokenscache_write_1h_tokenscache_read_tokensserver_tool_useweb_search_requests web_searchesoutput_tokens_detailsthinking_tokensoutput_reasoning_tokens output_tokensdefaultmodel)rootmappings api_flavor model_path prompt_tokens cached_tokenscompletion_tokens_detailsreasoning_tokenscompletion_tokenschatzclaude-2) starts_withz claude-v2)or_zClaude 2.0 / 2.1zClaude 2 is Anthropic's previous generation model, offering reliable performance for various tasks. This includes Claude 2.0 and Claude 2.1. i@ 824) input_mtok output_mtok)idmatchname descriptioncontext_windowpriceszclaude-3-5-haiku-latestzclaude-3-5-haikuzclaude-3.5-haikuzClaude Haiku 3.5z"Fastest, most cost-effective modelzOne-hour cache writes cost 2x the base input price. Ref: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricingz0.81z0.084z1.610)r0cache_write_mtokcache_read_mtokr1cache_write_1h_mtokweb_searches_kcount)r2r3r4r5r6price_commentsr7zclaude-3-5-sonnetzclaude-3.5-sonnetzClaude Sonnet 3.5zClaude 3.5 Sonnet is an ideal balance of intelligence and speed for enterprise workloads. Maximum utility at a lower price, dependable, balanced for scaled deployments.3z3.75z0.3156zclaude-3-7-sonnet-latestzclaude-3-7-sonnetzclaude-3.7-sonnetzclaude-sonnet-3.7zclaude-sonnet-3-7zClaude Sonnet 3.7zxClaude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities.zclaude-3-haikuzClaude Haiku 3z0.25z0.03z1.25z0.5)r0r;r<r1r=zclaude-3-opus-latestz claude-3-opusz Claude Opus 3zClaude 3 Opus was Anthropic's most powerful model for highly complex tasks. It boasts top-level performance, intelligence, fluency, and understanding.z18.75z1.57530zclaude-3-sonnetzClaude 3 SonnetzClaude 3 Sonnet is an ideal balance of intelligence and speed for enterprise workloads. Maximum utility at a lower price, dependable, balanced for scaled deployments.zclaude-fable-5)equalsz^claude-fable-5-\d{8}$)regexzClaude Fable 5z5For demanding reasoning and long-horizon agentic worki@BzFlat pricing across full 1M context window (no tiered pricing). Ref: https://platform.claude.com/docs/en/about-claude/pricing#long-context-pricing Prompt caching ref: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricingz12.55020zclaude-fable-5-1z^claude-fable-5-1-\d{8}$zClaude Fable 5.1zdAnthropic's most capable widely released model for demanding reasoning and long-horizon agentic workaGFlat pricing across full 1M context window (no tiered pricing). Cache hits are 0.025x base input (not the usual 0.1x), unique to Fable 5.1 and Mythos 5.1. Ref: https://platform.claude.com/docs/en/about-claude/pricing#model-pricing Prompt caching ref: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricingzclaude-haiku-4-5zclaude-haiku-4.5zclaude-4-5-haikuzclaude-4.5-haikuzClaude Haiku 4.5z(Fastest and most intelligent Haiku modelz0.152zclaude-opus-4-0z claude-4-opusz claude-opus-4zclaude-opus-4-20250514z Claude Opus 4z(Most intelligent model for complex taskszclaude-opus-4-1zclaude-opus-4.1zClaude Opus 4.1zclaude-opus-4-5zclaude-opus-4.5zclaude-4-5-opuszclaude-4.5-opuszClaude Opus 4.5zGPremium model combining maximum intelligence with practical performancez6.2525zclaude-opus-4-6zclaude-opus-4.6zclaude-4-6-opuszclaude-4.6-opuszClaude Opus 4.6z9Our most intelligent model for building agents and codingaOne-hour cache writes cost 2x the base input price. The 1M context window is generally available. Refs: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricing, https://platform.claude.com/docs/en/build-with-claude/context-windows#context-window-sizes-by-model)startprice)basetiersz37.5)r7i ) start_date) constraintr7zclaude-opus-4-7zclaude-opus-4.7zclaude-4-7-opuszclaude-4.7-opuszClaude Opus 4.7z?Our most capable model for complex reasoning and agentic codingzclaude-opus-4-8zclaude-opus-4.8zclaude-4-8-opuszclaude-4.8-opuszClaude Opus 4.8z claude-opus-5z^claude-opus-5-\d{8}$zclaude-opus-5.0z claude-5-opuszclaude-5.0-opusz Claude Opus 5z.For complex agentic coding and enterprise workaFFlat pricing across full 1M context window (no tiered pricing). Refs: https://platform.claude.com/docs/en/about-claude/pricing#long-context-pricing and https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool Prompt caching ref: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricingzclaude-opus-5-5z^claude-opus-5-5-\d{8}$zclaude-opus-5.5zclaude-5-5-opuszclaude-5.5-opuszClaude Opus 5.5z2For long-running agentic coding and knowledge worka6Flat pricing across full 1M context window (no tiered pricing). Cache hits are 0.05x base input (not the usual 0.1x), unique to Opus 5.5. Ref: https://platform.claude.com/docs/en/about-claude/pricing#model-pricing Prompt caching ref: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricingz0.2zclaude-sonnet-4-0zclaude-sonnet-4-2025zclaude-sonnet-4@zclaude-sonnet-4zclaude-4-sonnetzClaude Sonnet 4z0Optimal balance of intelligence, cost, and speedzclaude-sonnet-4-5zclaude-sonnet-4.5zClaude Sonnet 4.5z.Our best combination of speed and intelligenceaQOne-hour cache writes cost 2x the base input price. The 1M context beta was retired on 2026-04-30; requests over 200k now error. The >200k tiers describe historical usage from before retirement. Refs: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricing, https://platform.claude.com/docs/en/release-notes/overviewz7.5z0.6z22.512zclaude-sonnet-4-6zclaude-sonnet-4.6zClaude Sonnet 4.6zclaude-sonnet-5zclaude-sonnet-5.0zclaude-5-sonnetzclaude-5.0-sonnetzClaude Sonnet 5zLOur most agentic Sonnet model, approaching Opus 4.8 capability at lower costa^Flat pricing across the full 1M context window (no tiered pricing). Anthropic made the introductory $2/$10 per MTok rates permanent and cancelled the previously scheduled 2026-09-01 increase. Ref: https://platform.claude.com/docs/en/about-claude/pricing Prompt caching ref: https://platform.claude.com/docs/en/build-with-claude/prompt-caching#pricingz2.5z claude-v1z$Retired, here to match price sources)r2r3r5r7)r2r4 api_pattern pricing_urls model_matchprovider_match extractorsmodelsarceeArceezhttps://api\.arcee\.ai(?:/|$)z)https://docs.arcee.ai/get-started/pricingz"https://api.arcee.ai/api/v1/modelszBOpenAI-compatible hosted inference through the Arcee Platform API.aqCovers the complete public Text Models pricing table. The table publishes input, cached-input, and output token rates. Context windows and rates for images, requests, and cache writes are omitted because the public pricing page does not publish them. Model IDs use third-party namespaces, so they do not infer the Arcee provider without an Arcee provider ID or API URL.prompt_tokens_detailsz!deepseek/deepseek-v4-flash-latestzDeepSeek V4 Flashz0.14z0.028z0.28)r0r<r1)r2r3r4r7zdeepseek/deepseek-v4-prozDeepSeek V4 Proz1.74z3.48zmoonshotai/kimi-k3zKimi K3zthinkingmachines/inkling-smallz Inkling Smallz1.2ztrinity-large-thinkingzTrinity Large Thinkingz0.06zzai-org/glm-5.2zGLM 5.2z1.4z0.26z4.4) r2r4rUrVr5r?rXrYrZavianAvianzhttps://api\.avian\.iozhttps://avian.io/pricing/zPrices and model IDs checked against https://avian.io/docs/ on 2026-08-25. Cache prices use Avian's documented cache-read rates. The previously listed Meta Llama models are no longer in Avian's catalog and are deprecated.zMeta-Llama-3.1-405B-Instructz;No longer listed in Avian's model catalog as of 2026-08-25.)r2r3r? deprecatedr7zMeta-Llama-3.1-70B-Instructz0.45zMeta-Llama-3.1-8B-InstructzMeta-Llama-3.3-70B-Instructzdeepseek/deepseek-v3.2zDeepSeek V3.2 (Legacy)i|z0.23z0.012z0.33)r2r3r4r6r7zdeepseek/deepseek-v4-flashz0.0805z0.0165z0.161z1.305z0.10875z2.61zdeepseek/deepseek-v4-pro-0813zDeepSeek V4 Pro 0813z0.594z0.0198z1.782zminimax/minimax-m2.5z MiniMax M2.5iz0.27z0.15z1.08zmoonshotai/kimi-k2.5z Kimi K2.5ipz0.225z2.2zmoonshotai/kimi-k2.6z Kimi K2.6z0.95z0.16zxiaomi/mimo-v2.5zMiMo-V2.5 Smallz0.05z0.4zxiaomi/mimo-v2.5-proz MiMo-V2.5 Proz0.435z0.0036z0.87z z-ai/glm-4.7zGLM-4.7iz0.388z0.097z1.806z z-ai/glm-5zGLM-5i z0.516z0.129z2.322z z-ai/glm-5.1zGLM-5.1z0.743z0.186z2.971z z-ai/glm-5.2zGLM-5.2z0.495z0.124z1.733)r2r4rUrVr?rZawsz AWS Bedrockz8https://bedrock-runtime\.[a-z0-9-]+\.amazonaws\.com(/|$)z'https://aws.amazon.com/bedrock/pricing/bedrockamazon inputTokenscacheReadInputTokenscacheWriteInputTokens outputTokenszamazon.nova-2-sonic-v1:0zamazon.nova-2-sonicz Nova 2 Sonicz2.75)r0r1input_audio_mtokoutput_audio_mtokzamazon.nova-lite-v1:0zamazon.nova-litez Nova Litea&Amazon Nova Lite 1.0 is a very low-cost multimodal model from Amazon that focused on fast processing of image, video, and text inputs to generate text output. Amazon Nova Lite can handle real-time customer interactions, document analysis, and visual question-answering tasks with high accuracy.iz0.015z0.24zamazon.nova-micro-v1:0zamazon.nova-microz Nova MicroaAmazon Nova Micro 1.0 is a text-only model that delivers the lowest latency responses in the Amazon Nova family of models at a very low cost. With a context length of 128K tokens and optimized for speed and cost, Amazon Nova Micro excels at tasks such as text summarization, translation, content classification, interactive chat, and brainstorming. It has simple mathematical reasoning and coding abilities.iz0.035z0.00875zamazon.nova-premier-v1:0zamazon.nova-premierz Nova Premierz0.625zamazon.nova-pro-v1:0zamazon.nova-prozNova Proa7Amazon Nova Pro 1.0 is a capable multimodal model from Amazon focused on providing a combination of accuracy, speed, and cost for a wide range of tasks. As of December 2024, it achieves state-of-the-art performance on key benchmarks including visual question answering (TextVQA) and video understanding (VATEX).z3.2zamazon.nova-sonic-v1:0zamazon.nova-sonicz Nova Sonicz3.4z13.6zamazon.titan-embed-text-v1zamazon.titan-embed-textzTitan Embeddings G1 - Texti )r0zamazon.titan-text-express-v1ztitan-text-expresszTitan Text G1 - Expresszamazon.titan-text-lite-v1ztitan-text-litezTitan Text G1 - Litezdeepseek.r1-v1:0z deepseek.r1z DeepSeek-R1z1.35z5.4zglobal.amazon.nova-2-lite-v1:0zglobal.amazon.nova-2-litez Nova 2 Litez0.075z&global.anthropic.claude-fable-5-1-v1:0z!global.anthropic.claude-fable-5-1) ends_withz$global.anthropic.claude-fable-5-1-v1a!Global endpoint (no premium). Cache hits are 0.025x base input (not the usual 0.1x), unique to Fable 5.1 and Mythos 5.1. Ref: https://platform.claude.com/docs/en/about-claude/pricing#model-pricing Model ID ref: https://platform.claude.com/docs/en/build-with-claude/claude-in-amazon-bedrock)r0r;r<r1)r2r3r6r?r7z$global.anthropic.claude-fable-5-v1:0zglobal.anthropic.claude-fable-5z"global.anthropic.claude-fable-5-v1)r2r3r6r7z/global.anthropic.claude-haiku-4-5-20251001-v1:0z*global.anthropic.claude-haiku-4-5-20251001z%global.anthropic.claude-opus-4-5-v1:0z global.anthropic.claude-opus-4-5z%global.anthropic.claude-opus-4-6-v1:0z global.anthropic.claude-opus-4-6z%global.anthropic.claude-opus-4-7-v1:0z global.anthropic.claude-opus-4-7z%global.anthropic.claude-opus-4-8-v1:0z global.anthropic.claude-opus-4-8zglobal.anthropic.claude-opus-5z!global.anthropic.claude-opus-5-v1z global.anthropic.claude-opus-5-5z#global.anthropic.claude-opus-5-5-v1aGlobal endpoint (no premium). Cache hits are 0.05x base input (not the usual 0.1x), unique to Opus 5.5. Ref: AWS price list API, AmazonBedrockFoundationModels "Claude Opus 5.5 (Amazon Bedrock Edition)" (https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json) Model ID ref: https://platform.claude.com/docs/en/build-with-claude/claude-in-amazon-bedrockz.global.anthropic.claude-sonnet-4-20250514-v1:0z)global.anthropic.claude-sonnet-4-20250514z0global.anthropic.claude-sonnet-4-5-20250929-v1:0z+global.anthropic.claude-sonnet-4-5-20250929z'global.anthropic.claude-sonnet-4-6-v1:0z"global.anthropic.claude-sonnet-4-6z%global.anthropic.claude-sonnet-5-v1:0z global.anthropic.claude-sonnet-5zFlat pricing across the full 1M context window (no tiered pricing). The $2/$10 per MTok launch rates are now permanent, with no 2026-09-01 increase. Refs: https://aws.amazon.com/bedrock/pricing/, https://platform.claude.com/docs/en/about-claude/pricingzglobal.openai.gpt-5.6-lunazGPT-5.6 Luna (global)a4Global cross-Region inference, priced 10% below in-Region and Geo, and identical to OpenAI's own list price. Cross-Region inference for the GPT-5.6 models launched on 2026-08-17. Cache writes (30m TTL) are billed at 1.25x the input rate. At 272K input tokens and above, input and cache are 2x and output 1.5x. Tier starts are encoded as 271999 because the pricing engines select a tier when the token count is greater than start. The 80% Luna price cut of 2026-07-30 predates global availability, so there is no earlier global rate to record. Refs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-luna.html, https://aws.amazon.com/about-aws/whats-new/2026/08/amazon-bedrock-cross-region-openai-v2/, https://aws.amazon.com/about-aws/whats-new/2026/08/gpt-sol-terra-luna-long-context-bedrock/i&z0.02z0.04z1.8)r2r3r4r6r?r7zglobal.openai.gpt-5.6-solzGPT-5.6 Sol (global)aGlobal cross-Region inference, priced 10% below in-Region and Geo, and identical to OpenAI's own list price. Cross-Region inference launched 2026-08-17. Cache writes (30m TTL) are billed at 1.25x the input rate. At 272K input tokens and above, input and cache are 2x and output 1.5x. Tier starts are encoded as 271999 because the pricing engines select a tier when the token count is greater than start. AWS cut Sol input prices by 20% and output prices by 33.3% on 2026-08-21, quoting the global rates ($4 input, $20 output); the unconstrained entry keeps the four days of rates between global availability and the cut. Refs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-sol.html, https://aws.amazon.com/about-aws/whats-new/2026/08/bedrock-openai-gpt-56-sol-reduced-pricing/, https://aws.amazon.com/about-aws/whats-new/2026/08/amazon-bedrock-cross-region-openai-v2/, https://aws.amazon.com/about-aws/whats-new/2026/08/gpt-sol-terra-luna-long-context-bedrock/45zglobal.openai.gpt-5.6-terrazGPT-5.6 Terra (global)a6Global cross-Region inference, priced 10% below in-Region and Geo, and identical to OpenAI's own list price. Cross-Region inference for the GPT-5.6 models launched on 2026-08-17. Cache writes (30m TTL) are billed at 1.25x the input rate. At 272K input tokens and above, input and cache are 2x and output 1.5x. Tier starts are encoded as 271999 because the pricing engines select a tier when the token count is greater than start. The 20% Terra price cut of 2026-07-30 predates global availability, so there is no earlier global rate to record. Refs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-terra.html, https://aws.amazon.com/about-aws/whats-new/2026/08/amazon-bedrock-cross-region-openai-v2/, https://aws.amazon.com/about-aws/whats-new/2026/08/gpt-sol-terra-luna-long-context-bedrock/18zgoogle.gemma-3-12b-itzGemma 3 12B ITz0.09z0.29zgoogle.gemma-3-27b-itzGemma 3 27B ITz0.38zgoogle.gemma-3-4b-itz Gemma 3 4B ITzmeta.llama3-1-70b-instruct-v1:0zmeta.llama3-1-70b-instructzLlama 3.1 70B Instructz0.72zmeta.llama3-1-8b-instruct-v1:0zmeta.llama3-1-8b-instructzLlama 3.1 8B Instructz0.22zmeta.llama3-2-11b-instruct-v1:0zmeta.llama3-2-11b-instructzLlama 3.2 11B Instructzmeta.llama3-2-1b-instruct-v1:0zmeta.llama3-2-1b-instructzLlama 3.2 1B Instructzmeta.llama3-2-3b-instruct-v1:0zmeta.llama3-2-3b-instructzLlama 3.2 3B Instructzmeta.llama3-2-90b-instruct-v1:0zmeta.llama3-2-90b-instructzLlama 3.2 90B Instructzmeta.llama3-3-70b-instruct-v1:0zmeta.llama3-3-70b-instructzLlama 3.3 70B Instructzmeta.llama3-70b-instruct-v1:0zmeta.llama3-70b-instructzLlama 3 70B Instructz2.65z3.5zmeta.llama3-8b-instruct-v1:0zmeta.llama3-8b-instructzLlama 3 8B Instructz&meta.llama4-maverick-17b-instruct-v1:0z!meta.llama4-maverick-17b-instructzLlama 4 Maverick 17B Instructz0.97z#meta.llama4-scout-17b-instruct-v1:0zmeta.llama4-scout-17b-instructzLlama 4 Scout 17B Instructiz0.17z0.66zmistral.devstral-2-123bzDevstral 2 123Bizmistral.magistral-small-2509zMagistral Small 2509z mistral.ministral-3-14b-instructzMinistral 14B 3.0zmistral.ministral-3-3b-instructzMinistral 3B 3.0zmistral.ministral-3-8b-instructzMinistral 8B 3.0z mistral.mistral-7b-instruct-v0:2zmistral.mistral-7b-instruct-v0zMistral 7B Instructi}zmistral.mistral-large-2402-v1:0zmistral.mistral-large-2402zMistral Large (24.02)z%mistral.mistral-large-3-675b-instructzMistral Large 3zmistral.mistral-small-2402-v1:0zmistral.mistral-small-2402zMistral Small (24.02)z"mistral.mixtral-8x7b-instruct-v0:1z mistral.mixtral-8x7b-instruct-v0zMixtral 8x7B Instructz0.7zmistral.pixtral-large-2502-v1:0zmistral.pixtral-large-2502zPixtral Large (25.02)zmistral.voxtral-mini-3b-2507zVoxtral Mini 3B 2507zmistral.voxtral-small-24b-2507zVoxtral Small 24B 2507znvidia.nemotron-nano-3-30b:0znvidia.nemotron-nano-3-30bzNemotron 3 Nano 30Bznvidia.nemotron-nano-9b-v2:0znvidia.nemotron-nano-9b-v2zNemotron 2 Nano 9Bznvidia.nemotron-super-3-120b:0znvidia.nemotron-super-3-120bzNemotron 3 Super 120Bz0.65zopenai.gpt-5.4zGPT-5.4z0.275z16.5zopenai.gpt-5.5zGPT-5.5z5.5z0.5533zopenai.gpt-oss-120b-1:0zopenai.gpt-oss-120b-1z gpt-oss-120bzopenai.gpt-oss-20b-1:0zopenai.gpt-oss-20b-1z gpt-oss-20bz0.07zqwen.qwen3-32b-v1:0zqwen.qwen3-32bzQwen3 32B (dense)zqwen.qwen3-coder-30b-a3b-v1:0zqwen.qwen3-coder-30b-a3bzQwen3-Coder-30B-A3B-Instructzqwen.qwen3-coder-480b-a35b-v1:0zqwen.qwen3-coder-480b-a35bzQwen3-Coder-480B-A35B-Instructzqwen.qwen3-vl-235b-a22b-v1:0zqwen.qwen3-vl-235b-a22bzQwen3-VL-235B-A22B-Instructz0.53z2.66z regional.amazon.nova-2-lite-v1:0zus.amazon.nova-2-litezeu.amazon.nova-2-litezjp.amazon.nova-2-liteaAmazon Nova 2 Lite is an advanced multimodal reasoning model that intelligently balances performance and efficiency by dynamically adjusting reasoning depth based on task complexity. With flexible controls for developers to adjust the reasoning process, Nova 2 Lite delivers superior results for agentic workflows across software development, consumer experiences and enterprise application.z0.0825z1regional.anthropic.claude-3-5-haiku-20241022-v1:0zclaude-3-5-haiku-20241022z2regional.anthropic.claude-3-5-sonnet-20240620-v1:0zclaude-3-5-sonnet-20240620z2regional.anthropic.claude-3-5-sonnet-20241022-v2:0zclaude-3-5-sonnet-20241022z2regional.anthropic.claude-3-7-sonnet-20250219-v1:0zclaude-3-7-sonnet-20250219z/regional.anthropic.claude-3-haiku-20240307-v1:0zclaude-3-haiku-20240307z.regional.anthropic.claude-3-opus-20240229-v1:0zclaude-3-opus-20240229z0regional.anthropic.claude-3-sonnet-20240229-v1:0zclaude-3-sonnet-20240229z(regional.anthropic.claude-fable-5-1-v1:0zanthropic.claude-fable-5-1zanthropic.claude-fable-5-1-v1zclaude-fable-5-1-v1z us.anthropic.claude-fable-5-1-v1aRegional endpoint: 10% premium over the global endpoint. Fable 5.1 regional is currently us-east-1 only. Cache hits are 0.025x base input (not the usual 0.1x), unique to Fable 5.1 and Mythos 5.1. Ref: https://platform.claude.com/docs/en/build-with-claude/claude-in-amazon-bedrock#regions11z13.7555z®ional.anthropic.claude-fable-5-v1:0zanthropic.claude-fable-5zanthropic.claude-fable-5-v1zclaude-fable-5-v1zus.anthropic.claude-fable-5-v1zau.anthropic.claude-fable-5-v1zeu.anthropic.claude-fable-5-v1zjp.anthropic.claude-fable-5-v1z1.1z1regional.anthropic.claude-haiku-4-5-20251001-v1:0z#anthropic.claude-haiku-4-5-20251001zclaude-haiku-4-5-20251001z&us.anthropic.claude-haiku-4-5-20251001z&au.anthropic.claude-haiku-4-5-20251001z(apac.anthropic.claude-haiku-4-5-20251001z&eu.anthropic.claude-haiku-4-5-20251001z*us-gov.anthropic.claude-haiku-4-5-20251001z&jp.anthropic.claude-haiku-4-5-20251001z1.375z0.11z0regional.anthropic.claude-opus-4-1-20250805-v1:0z"anthropic.claude-opus-4-1-20250805zclaude-opus-4-1-20250805z%us.anthropic.claude-opus-4-1-20250805z%au.anthropic.claude-opus-4-1-20250805z'apac.anthropic.claude-opus-4-1-20250805z%eu.anthropic.claude-opus-4-1-20250805z)us-gov.anthropic.claude-opus-4-1-20250805z%jp.anthropic.claude-opus-4-1-20250805z.regional.anthropic.claude-opus-4-20250514-v1:0z anthropic.claude-opus-4-20250514z#us.anthropic.claude-opus-4-20250514z#au.anthropic.claude-opus-4-20250514z%apac.anthropic.claude-opus-4-20250514z#eu.anthropic.claude-opus-4-20250514z'us-gov.anthropic.claude-opus-4-20250514z#jp.anthropic.claude-opus-4-20250514z'regional.anthropic.claude-opus-4-5-v1:0zanthropic.claude-opus-4-5zus.anthropic.claude-opus-4-5zau.anthropic.claude-opus-4-5zapac.anthropic.claude-opus-4-5zeu.anthropic.claude-opus-4-5z us-gov.anthropic.claude-opus-4-5zjp.anthropic.claude-opus-4-5z6.875z27.5z'regional.anthropic.claude-opus-4-6-v1:0zanthropic.claude-opus-4-6zus.anthropic.claude-opus-4-6zau.anthropic.claude-opus-4-6zapac.anthropic.claude-opus-4-6zeu.anthropic.claude-opus-4-6z us-gov.anthropic.claude-opus-4-6zjp.anthropic.claude-opus-4-6z'regional.anthropic.claude-opus-4-7-v1:0zanthropic.claude-opus-4-7zus.anthropic.claude-opus-4-7zau.anthropic.claude-opus-4-7zapac.anthropic.claude-opus-4-7zeu.anthropic.claude-opus-4-7z us-gov.anthropic.claude-opus-4-7zjp.anthropic.claude-opus-4-7z'regional.anthropic.claude-opus-4-8-v1:0zanthropic.claude-opus-4-8zus.anthropic.claude-opus-4-8zau.anthropic.claude-opus-4-8zeu.anthropic.claude-opus-4-8zjp.anthropic.claude-opus-4-8z regional.anthropic.claude-opus-5zanthropic.claude-opus-5zanthropic.claude-opus-5-v1zclaude-opus-5-v1zus.anthropic.claude-opus-5zau.anthropic.claude-opus-5zeu.anthropic.claude-opus-5zjp.anthropic.claude-opus-5zus.anthropic.claude-opus-5-v1zau.anthropic.claude-opus-5-v1zeu.anthropic.claude-opus-5-v1zjp.anthropic.claude-opus-5-v1zRegional endpoints and US/EU/JP/AU inference profiles carry a 10% premium over the global endpoint. Ref: https://platform.claude.com/docs/en/build-with-claude/claude-in-amazon-bedrock#regionsz"regional.anthropic.claude-opus-5-5zanthropic.claude-opus-5-5zanthropic.claude-opus-5-5-v1zclaude-opus-5-5-v1zus.anthropic.claude-opus-5-5zau.anthropic.claude-opus-5-5zeu.anthropic.claude-opus-5-5zjp.anthropic.claude-opus-5-5zus.anthropic.claude-opus-5-5-v1zau.anthropic.claude-opus-5-5-v1zeu.anthropic.claude-opus-5-5-v1zjp.anthropic.claude-opus-5-5-v1aRegional endpoints and US/EU/JP/AU inference profiles carry a 10% premium over the global endpoint. Cache hits are 0.05x base input (not the usual 0.1x), unique to Opus 5.5. Ref: AWS price list API, AmazonBedrockFoundationModels "Claude Opus 5.5 (Amazon Bedrock Edition)" (https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json)22z8.8z0regional.anthropic.claude-sonnet-4-20250514-v1:0z"anthropic.claude-sonnet-4-20250514zclaude-sonnet-4-20250514z%us.anthropic.claude-sonnet-4-20250514z%au.anthropic.claude-sonnet-4-20250514z'apac.anthropic.claude-sonnet-4-20250514z%eu.anthropic.claude-sonnet-4-20250514z)us-gov.anthropic.claude-sonnet-4-20250514z%jp.anthropic.claude-sonnet-4-20250514z2regional.anthropic.claude-sonnet-4-5-20250929-v1:0z$anthropic.claude-sonnet-4-5-20250929zclaude-sonnet-4-5-20250929z'us.anthropic.claude-sonnet-4-5-20250929z'au.anthropic.claude-sonnet-4-5-20250929z)apac.anthropic.claude-sonnet-4-5-20250929z'eu.anthropic.claude-sonnet-4-5-20250929z+us-gov.anthropic.claude-sonnet-4-5-20250929z'jp.anthropic.claude-sonnet-4-5-20250929z3.3z4.125z)regional.anthropic.claude-sonnet-4-6-v1:0zanthropic.claude-sonnet-4-6zus.anthropic.claude-sonnet-4-6zau.anthropic.claude-sonnet-4-6z apac.anthropic.claude-sonnet-4-6zeu.anthropic.claude-sonnet-4-6z"us-gov.anthropic.claude-sonnet-4-6zjp.anthropic.claude-sonnet-4-6z'regional.anthropic.claude-sonnet-5-v1:0zanthropic.claude-sonnet-5zus.anthropic.claude-sonnet-5zau.anthropic.claude-sonnet-5zapac.anthropic.claude-sonnet-5zeu.anthropic.claude-sonnet-5z us-gov.anthropic.claude-sonnet-5zjp.anthropic.claude-sonnet-5zRegional/cross-region endpoints carry a 10% premium over global. The launch rates are now permanent, with no 2026-09-01 increase. Refs: https://aws.amazon.com/bedrock/pricing/, https://platform.claude.com/docs/en/about-claude/pricingzregional.openai.gpt-5.6-lunazopenai.gpt-5.6-lunaz gpt-5.6-lunazus.openai.gpt-5.6-lunazin.openai.gpt-5.6-lunazGPT-5.6 Luna (regional)aIn-Region and Geo (`us.`/`in.`) inference, 10% above global. Cache writes (30m TTL) are billed at 1.25x input; at 272K input tokens and above, input and cache are 2x and output 1.5x. Tier starts are encoded as 271999 because the pricing engines select a tier when the token count is greater than start. AWS cut Luna prices by 80% on 2026-07-30; the unconstrained entry preserves the launch (2026-07-13) rates. The long-context tier arrived with the 1M context window on 2026-08-03, so the launch entry stays flat. Refs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-luna.html, https://aws.amazon.com/about-aws/whats-new/2026/07/openai-gpt-terra-luna-pricing-bedrock/, https://aws.amazon.com/about-aws/whats-new/2026/08/gpt-sol-terra-luna-long-context-bedrock/z6.6z0.44z0.022z0.044z1.32z1.98zregional.openai.gpt-5.6-solzopenai.gpt-5.6-solz gpt-5.6-solzus.openai.gpt-5.6-solzGPT-5.6 Sol (regional)aIn-Region and Geo (`us.`) inference, 10% above global. Cache writes (30m TTL) are billed at 1.25x input; at 272K input tokens and above, input and cache are 2x and output 1.5x. Tier starts are encoded as 271999 because the pricing engines select a tier when the token count is greater than start. Sol input prices fell 20% and output prices 33.3% on 2026-08-21; the announcement quotes the global rates, and the in-Region and Geo rates moved with them. Refs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-sol.html, https://aws.amazon.com/about-aws/whats-new/2026/08/bedrock-openai-gpt-56-sol-reduced-pricing/, https://aws.amazon.com/about-aws/whats-new/2026/08/gpt-sol-terra-luna-long-context-bedrock/z49.5z0.88zregional.openai.gpt-5.6-terrazopenai.gpt-5.6-terraz gpt-5.6-terrazus.openai.gpt-5.6-terrazin.openai.gpt-5.6-terrazGPT-5.6 Terra (regional)aIn-Region and Geo (`us.`/`in.`) inference, 10% above global. Cache writes (30m TTL) are billed at 1.25x input; at 272K input tokens and above, input and cache are 2x and output 1.5x. Tier starts are encoded as 271999 because the pricing engines select a tier when the token count is greater than start. AWS cut Terra prices by 20% on 2026-07-30; the unconstrained entry preserves the launch (2026-07-13) rates. The long-context tier arrived with the 1M context window on 2026-08-03, so the launch entry stays flat. Refs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-terra.html, https://aws.amazon.com/about-aws/whats-new/2026/07/openai-gpt-terra-luna-pricing-bedrock/, https://aws.amazon.com/about-aws/whats-new/2026/08/gpt-sol-terra-luna-long-context-bedrock/z3.4375z13.2z19.8zwriter.palmyra-x4-v1:0zwriter.palmyra-x4z Palmyra X4zBedrock serves Palmyra X4 through cross-region inference profiles, so the model reference arrives prefixed, e.g. 'us.writer.palmyra-x4-v1:0'. Pricing is flat across regions. Ref: https://aws.amazon.com/bedrock/pricing/zwriter.palmyra-x5-v1:0zwriter.palmyra-x5z Palmyra X5zBedrock serves Palmyra X5 through cross-region inference profiles, so the model reference arrives prefixed, e.g. 'us.writer.palmyra-x5-v1:0'. Pricing is flat across regions. Ref: https://aws.amazon.com/bedrock/pricing/)r2r4rUrVrXrYrZazurezMicrosoft Azurezr(https?://)?([^.]*\.)?(?:openai\.azure\.com|azure-api\.net|cognitiveservices\.azure\.com|services\.ai\.azure\.com)z\https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/#pricingzThese are prices for "*-Global" models, prices for "Regional" models are often slightly higher. Retired models are listed at https://learn.microsoft.com/th-th/azure/ai-foundry/openai/concepts/legacy-models audio_tokensinput_audio_tokensoutput_audio_tokensinput_tokens_details responsesresponseinput_token_details text_tokensinput_text_tokens image_tokensinput_image_tokens)r|cached_tokens_detailsr}cache_text_read_tokens)r|rrvcache_audio_read_tokens)r|rrcache_image_read_tokensoutput_token_detailsoutput_text_tokensrealtime embeddings)openairdeepseekx-ai moonshotaiadaztext-embedding-adaztext-embedding-ada-002ztext-embedding-ada-002-v2)r2r3r7babbagez babbage-002curiez text-curieztext-curie-001davinciz davinci-002z text-davinciztext-davinci-002zmai-ds-r1:freezMAI DS R1 (free)aMAI-DS-R1 is a post-trained variant of DeepSeek-R1 developed by the Microsoft AI team to improve the model's responsiveness on previously blocked topics while enhancing its safety profile. Built on top of DeepSeek-R1's reasoning foundation, it integrates 110k examples from the Tulu-3 SFT dataset and 350k internally curated multilingual safety-alignment samples. The model retains strong reasoning, coding, and problem-solving capabilities, while unblocking a wide range of prompts previously restricted in R1.io1z o1-2024-12-1760zo1-minizo1-mini-2024-09-12z o1-previewzo1-preview-2024-09-12z o3-2025-04-16o3zo3-minizo3-mini-2025-01-31zo4-minizo4-mini-2025-04-16zphi-3-medium-128k-instructzPhi-3 Medium 128K Instructa3Phi-3 128K Medium is a powerful 14-billion parameter model designed for advanced language understanding, reasoning, and instruction following. Optimized through supervised fine-tuning and preference adjustments, it excels in tasks involving common sense, mathematics, logical reasoning, and code processing.izphi-3-mini-128k-instructzPhi-3 Mini 128K Instructa&Phi-3 Mini is a powerful 3.8B parameter model designed for advanced language understanding, reasoning, and instruction following. Optimized through supervised fine-tuning and preference adjustments, it excels in tasks involving common sense, mathematics, logical reasoning, and code processing.zphi-3.5-mini-128k-instructzPhi-3.5 Mini 128K InstructavPhi-3.5 models are lightweight, state-of-the-art open models. These models were trained with Phi-3 datasets that include both synthetic data and the filtered, publicly available websites data, with a focus on high quality and reasoning-dense properties. Phi-3.5 Mini uses 3.8B parameters, and is a dense decoder-only transformer model using the same tokenizer as Phi-3 Mini.zphi-4zPhi 4zMicrosoft Research Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed.i@zphi-4-mini-instructzPhi 4 Mini InstructzPhi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites, with a focus on high-quality, reasoning-dense data.zcImported from OpenRouter pricing; verify against Azure AI Foundry when native pricing is published.z0.35zphi-4-multimodal-instructzPhi 4 Multimodal Instructa&Phi-4 Multimodal Instruct is a versatile 5.6B parameter foundation model that combines advanced reasoning and instruction-following capabilities across both text and visual inputs, providing accurate text outputs. The unified architecture enables efficient, low-latency inference, suitable for edge and mobile deployments. Phi-4 Multimodal Instruct supports text inputs in multiple languages including Arabic, Chinese, English, French, German, Japanese, Spanish, and more, with visual input optimized primarily for English. It delivers impressive performance on multimodal tasks involving mathematical, scientific, and document reasoning, providing developers and enterprises a powerful yet compact model for sophisticated interactive applications. For more information, see the Phi-4 Multimodal blog post.zphi-4-reasoning-pluszPhi 4 Reasoning Plusa{Phi-4-reasoning-plus is an enhanced 14B parameter model from Microsoft, fine-tuned from Phi-4 with additional reinforcement learning to boost accuracy on math, science, and code reasoning tasks. It uses the same dense decoder-only transformer architecture as Phi-4, but generates longer, more comprehensive outputs structured into a step-by-step reasoning trace and final answer.izphi-4-reasoning-plus:freezPhi 4 Reasoning Plus (free)zphi-4-reasoning:freezPhi 4 Reasoning (free)aPhi-4-reasoning is a 14B parameter dense decoder-only transformer developed by Microsoft, fine-tuned from Phi-4 to enhance complex reasoning capabilities. It uses a combination of supervised fine-tuning on chain-of-thought traces and reinforcement learning, targeting math, science, and code reasoning tasks. With a 32k context window and high inference efficiency, it is optimized for structured responses in a two-part format: reasoning trace followed by a final solution.ztext-embedding-3-largez0.13ztext-embedding-3-smallzwizardlm-2-8x22bzWizardLM-2 8x22BzWizardLM-2 8x22B is Microsoft AI's most advanced Wizard model. It demonstrates highly competitive performance compared to leading proprietary models, and it consistently outperforms all existing state-of-the-art opensource models.z0.48)r2r3r4r5r7)r2r4rUrVr?rYfallback_model_providersrZbasetenBasetenz%https://inference\.baseten\.co(?:/|$)zhttps://www.baseten.co/pricing/z5https://docs.baseten.co/inference/model-apis/overviewzMOpenAI- and Anthropic-compatible hosted inference through Baseten Model APIs.a`Covers the complete public Model APIs pricing table. Baseten automatically caches prompt prefixes and bills cached input at the published cache-input rate. Context windows use the catalog's displayed values in thousands of tokens. Model IDs use third-party namespaces, so they do not infer the Baseten provider without a Baseten provider ID or API URL.z"deepseek-ai/DeepSeek-V4-Flash-0731zDeepSeek V4 Flash 0731izdeepseek-ai/DeepSeek-V4-Proz0.145z deepseek-ai/DeepSeek-V4-Pro-0813z0.132z3.96zmoonshotai/Kimi-K2.6zmoonshotai/Kimi-K2.7-CodezKimi K2.7 Codezmoonshotai/Kimi-K3z(nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55BzNVIDIA Nemotron 3 Ultraz0.12z2.4zopenai/gpt-oss-120bz GPT OSS 120BzOThe pricing table does not publish a separate cached-input rate for this model.zthinkingmachines/inklingInklingz4.05zzai-org/GLM-4.7zGLM 4.7zzai-org/GLM-5.2zzai-org/GLM-5.2-Fastz GLM 5.2 Fastz2.1z0.21zzai-org/GLM-5.3zGLM 5.3zzai-org/GLM-5.3-Flashz GLM 5.3 FlashcerebrasCerebraszhttps://api\.cerebras\.ai)z'https://www.cerebras.ai/pricing#pricingz4https://inference-docs.cerebras.ai/models/openai-ossz5https://inference-docs.cerebras.ai/models/gemma-4-31bz5https://inference-docs.cerebras.ai/support/change-logz gemma-4-31bzcerebras/gemma-4-31bzcerebras:gemma-4-31bz Gemma 4 31BzGoogle's Gemma 4 31B open model for chat, instruction following, and multilingual tasks, served with fast inference on Cerebras hardware (~1,850 tokens/second).zHDeveloper tier pricing. Free tier: 65k context, Paid tier: 131k context.z0.99z1.49zcerebras/gpt-oss-120bzcerebras:gpt-oss-120bz GPT-OSS 120BzOpenAI's flagship open source model, built on a Mixture-of-Experts (MoE) architecture with 120 billion parameters and 128 experts. Delivers frontier reasoning capabilities with record-breaking inference speeds on Cerebras hardware (~3,000 tokens/second).z0.75z llama-3.3-70bzcerebras/llama-3.3-70bzcerebras:llama-3.3-70bz Llama 3.3 70BzMeta's enhanced 70B model delivering 405B-level accuracy. Optimized for chat, coding, instruction following, mathematics, and reasoning with high-speed inference on Cerebras hardware (~2,100 tokens/second).zNo longer listed in the Cerebras Inference docs (checked 2026-07-17 and 2026-08-27); last known rates kept for historical usage.z0.85)r2r3r4r5r6r?r`r7z llama3.1-8bzcerebras/llama3.1-8bzcerebras:llama3.1-8bz Llama 3.1 8BzMeta's Llama 3.1 8B model for general-purpose tasks including chat, coding, and instruction following. Optimized for fast inference on Cerebras hardware (~2,200 tokens/second).z qwen-3-32bzcerebras/qwen-3-32bzcerebras:qwen-3-32bz Qwen 3 32BzQwen's 32B parameter model with enhanced reasoning and coding capabilities. Supports both standard and reasoning modes for complex tasks, with fast inference speeds on Cerebras hardware (~2,600 tokens/second).zqwen-3-coder-480bzDSeems to be no longer available on cerebras, here to help with tests)r2r3r4r?r7z zai-glm-4.7zcerebras/zai-glm-4.7zcerebras:zai-glm-4.7z Z.ai GLM 4.7zZ.ai's GLM 4.7, a 355 billion parameter model with reasoning enabled by default, served with fast inference on Cerebras hardware (~1,000 tokens/second).zDeprecated by Cerebras on 2026-08-17 (see https://inference-docs.cerebras.ai/support/change-log) and no longer in the model catalog; last published developer tier rates kept for historical usage.z2.25 cloudflarezCloudflare Workers AIz?https://api\.cloudflare\.com/client/v4/accounts/[^/]+/ai(?:/|$)z>https://developers.cloudflare.com/workers-ai/platform/pricing/z4https://developers.cloudflare.com/workers-ai/models/aPaid Workers plan rates, expressed using Cloudflare's token-equivalent prices. Calculations do not apply the account-wide free allocation of 10,000 Neurons per day. This provider entry deliberately covers only models with token-equivalent prices. Image and audio models are omitted.z@cf/resultz%@cf/ai4bharat/indictrans2-en-indic-1BzIndicTrans2 EN-Indic 1Bz0.342z(@cf/aisingapore/gemma-sea-lion-v4-27b-itzGemma SEA-LION v4 27B ITz0.351z0.555z@cf/baai/bge-base-en-v1.5zBGE Base English v1.5z0.067z@cf/baai/bge-large-en-v1.5zBGE Large English v1.5z0.204z@cf/baai/bge-m3zBGE-M3z@cf/baai/bge-reranker-basezBGE Reranker Basez0.003z@cf/baai/bge-small-en-v1.5zBGE Small English v1.5z,@cf/deepseek-ai/deepseek-r1-distill-qwen-32bzDeepSeek R1 Distill Qwen 32Bz0.497z4.881z&@cf/deepseek-ai/deepseek-v4-flash-0731z0.014z$@cf/deepseek-ai/deepseek-v4-pro-0813z@cf/google/gemma-3-12b-itz0.345z0.556)r2r3r4r`r7z@cf/google/gemma-4-26b-a4b-itzGemma 4 26B A4B ITz%@cf/huggingface/distilbert-sst-2-int8zDistilBERT SST-2 INT8z0.026z#@cf/ibm-granite/granite-4.0-h-microzGranite 4.0 H Microz0.017z0.112z@cf/meta/llama-2-7b-chat-fp16zLlama 2 7B Chat FP16z6.667z@cf/meta/llama-3-8b-instructz0.282z0.827z @cf/meta/llama-3-8b-instruct-awqzLlama 3 8B Instruct AWQz0.123z0.266z(@cf/meta/llama-3.1-70b-instruct-fp8-fastzLlama 3.1 70B Instruct FP8 Fastz0.293z2.253z@cf/meta/llama-3.1-8b-instructz"@cf/meta/llama-3.1-8b-instruct-awqzLlama 3.1 8B Instruct AWQz"@cf/meta/llama-3.1-8b-instruct-fp8zLlama 3.1 8B Instruct FP8z0.152z0.287z'@cf/meta/llama-3.1-8b-instruct-fp8-fastz#@cf/meta/llama-3.1-8b-instruct-fastzLlama 3.1 8B Instruct FP8 FastznCloudflare's pricing table uses the fp8-fast identifier while the model catalog documents the fast identifier.z0.045z0.384z&@cf/meta/llama-3.2-11b-vision-instructzLlama 3.2 11B Vision Instructz0.049z0.676z@cf/meta/llama-3.2-1b-instructz0.027z0.201z@cf/meta/llama-3.2-3b-instructz0.051z0.335z(@cf/meta/llama-3.3-70b-instruct-fp8-fastzLlama 3.3 70B Instruct FP8 Fasti]z'@cf/meta/llama-4-scout-17b-16e-instructzLlama 4 Scout 17B 16E Instructz@cf/meta/llama-guard-3-8bzLlama Guard 3 8Bz0.484z@cf/meta/m2m100-1.2bz M2M100 1.2Bz$@cf/mistral/mistral-7b-instruct-v0.1zMistral 7B Instruct v0.1z0.19z,@cf/mistralai/mistral-small-3.1-24b-instructzMistral Small 3.1 24B Instructz!@cf/moondream/moondream3.1-9B-A2BzMoondream 3.1 9B A2Bz@cf/moonshotai/kimi-k2.5z@cf/moonshotai/kimi-k2.6z@cf/moonshotai/kimi-k2.7-codez@cf/nvidia/nemotron-3-120b-a12bzNemotron 3 120B A12Bz@cf/openai/gpt-oss-120bz@cf/openai/gpt-oss-20bz GPT-OSS 20Bz@cf/pfnet/plamo-embedding-1bzPLaMo Embedding 1Bz0.019z#@cf/qwen/qwen2.5-coder-32b-instructzQwen2.5 Coder 32B Instructz@cf/qwen/qwen3-30b-a3b-fp8zQwen3 30B A3B FP8z@cf/qwen/qwen3-embedding-0.6bzQwen3 Embedding 0.6Bz@cf/qwen/qwen3.8-27bz Qwen3.8 27Biz@cf/qwen/qwq-32bzQwQ 32Bz@cf/zai-org/glm-4.7-flashz GLM 4.7 Flashz@cf/zai-org/glm-5.2z@cf/zai-org/glm-5.3-flash) r2r4rUrVr?rWrXrYrZcohereCoherezhttps://api\.cohere\.(?:ai|com)zhttps://cohere.com/pricingzcommand- billed_unitstokensmetazc4ai-aya-expanse-32bzaya-expanse-32bzAya Expanse 32BzAya Expanse is a highly performant 32B multilingual model, designed to rival monolingual performance through innovations in instruction tuning with data arbitrage, preference training, and model merging. Serves 23 languages.zhttps://cohere.com/pricing FAQ: Aya Expanse models (8B and 32B) on the API are charged at $0.50/1M tokens for input and $1.50/1M tokens for output.zc4ai-aya-expanse-8bzaya-expanse-8bzAya Expanse 8BzAya Expanse is a highly performant 8B multilingual model, designed to rival monolingual performance through innovations in instruction tuning with data arbitrage, preference training, and model merging. Serves 23 languages.zRetired 2026-04-04 per https://docs.cohere.com/docs/models; last published price kept for historical usage. https://cohere.com/pricing FAQ: Aya Expanse models (8B and 32B) on the API are charged at $0.50/1M tokens for input and $1.50/1M tokens for output.commandCommandzCommand is an instruction-following conversational model that performs language tasks with high quality, more reliably and with a longer context than our base generative models.z command-azcommand-a-03-2025z Command AaiCommand A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary and open-weights models Command A delivers maximum performance with minimum hardware costs, excelling on business-critical agentic and multilingual tasks.z command-lightz Command LightzJA smaller, faster version of Command. Almost as capable, but a lot faster.izDeprecated 2025-09-15 per https://docs.cohere.com/docs/models; still billable for existing customers. https://cohere.com/pricing FAQ: Command-light pricing is $0.30/1M tokens for input and $0.60/1M tokens for output.z command-rzcommand-r-08-2024z Command RaCommand-R is a 35B parameter model that performs conversational language tasks at a higher quality, more reliably, and with a longer context than previous models. It can be used for complex workflows like code generation, retrieval augmented generation (RAG), tool use, and agents.zcommand-r-pluszcommand-r-plus-08-2024z Command R+zCommand R+ is a new, 104B-parameter LLM from Cohere. It's useful for roleplay, general consumer usecases, and Retrieval Augmented Generation (RAG).z command-r7bzcommand-r7b-12-2024z Command R7BzCommand R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning and multiple steps.z0.0375z embed-v4.0z Embed v4.0zEmbed v4.0 is a state-of-the-art embedding model designed for precise retrieval across noisy, multilingual, and multimodal data.cursorCursorzhttps://api\.cursor\.com)z*https://cursor.com/docs/models-and-pricingz'https://cursor.com/docs/models/grok-4-6z'https://cursor.com/docs/models/grok-4-5z2https://cursor.com/docs/models/cursor-composer-2-5zSAgentic coding models available through Cursor's editor, SDK, and Cloud Agents API.z composer- tokenUsagecacheWriteTokenscacheReadTokensz usage-eventz composer-2.5z^composer-2\.5\[fast=false\]$z Composer 2.5zMCursor's agentic coding model, optimized for long-running tasks and tool use.z>Standard on-demand usage. Fast is a separately priced variant.zcomposer-2.5-fastz^composer-2\.5\[fast=true\]$zComposer 2.5 Fastz@Faster Composer 2.5 speed tier with the same model intelligence.zFast on-demand usage.zgrok-4.5z^grok-4\.5\[fast=false\]$zGrok 4.5zOCursor and SpaceXAI's agentic model for long-running coding and knowledge work.z grok-4.5-fastz^grok-4\.5\[fast=true\]$z Grok 4.5 FastzAFaster Grok 4.5 speed tier for agentic coding and knowledge work.zgrok-4.6z^grok-4\.6\[fast=false\]$zGrok 4.6zKCursor and SpaceXAI's frontier model for complex coding and knowledge work.z grok-4.6-fastz^grok-4\.6\[fast=true\]$z Grok 4.6 FastzAFaster Grok 4.6 speed tier for complex coding and knowledge work.)r2r4rUrVr5rWrYrZrDeepseekzhttps://api\.deepseek\.comz1https://api-docs.deepseek.com/quick_start/pricingzDeepseek off-peak pricing applies "UTC 16:30-00:30" so we switch it around and use the off-peak pricing as the default (first) price then the second price with a constraint is the "standard" pricing that applies "UTC 00:30-16:30".z deepseek-chatzdeepseek-chat-v3-0324z DeepSeek Chata5DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. Pre-trained on nearly 15 trillion tokens, the reported evaluations reveal that the model outperforms other open-source models and rivals leading closed-source models.iz0.135)tzinfo) start_timeend_timezdeepseek-reasonerz deepseek-r1zdeepseek-r1-0528z Deepseek R1zDeepSeek R1 is here: Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.z2.19zdeepseek-v3.1-terminuszDeepSeek V3.1 TerminuszDeepSeek-V3.1 Terminus is an update to DeepSeek V3.1 that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities.z deepseek-v3.2z DeepSeek V3.2zDeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance.z0.2288z0.3432zdeepseek-v3.2-expzDeepSeek V3.2 ExpzDeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures.z0.41zdeepseek-v4-flashzDeepSeek-V4-Flash. Supports both non-thinking and thinking (default) modes, JSON output, tool calls, chat prefix completion, and FIM completion (non-thinking only).a}From 2026-08-17 the V4 models use different peak windows from the V3 models: peak is "UTC 01:00-04:00" and "UTC 06:00-10:00", everything else is off-peak. The flat rate that applied before 2026-08-17 is kept as the unconstrained first price, the new off-peak rate is gated on start_date, and the two peak windows come last so they win during peak hours. Two things this layout still cannot say, because `constraint` is a union and one entry cannot carry both a date and a daily window. Requests from before 2026-08-17 that fall inside 01:00-04:00 or 06:00-10:00 UTC - 7 hours of every day - resolve to the new peak rate rather than the old flat rate. And from 2026-08-23 Deepseek bills off-peak all day at weekends (Beijing time), which needs a day-of-week condition, so on Saturdays and Sundays the peak prices here are an upper bound. See https://github.com/pydantic/genai-prices/issues/582.z0.0028z0.007 zdeepseek-v4-prozDeepSeek-V4-Pro. Supports both non-thinking and thinking (default) modes, JSON output, tool calls, chat prefix completion, and FIM completion (non-thinking only).z0.003625)r2r4rUrVr?rWrYrZ doubleword Doublewordzhttps://api\.doubleword\.aiz/https://docs.doubleword.ai/inference-api/modelsznDoubleword publishes Realtime, Async, and Batch prices. This provider currently encodes only Realtime pricing.zQwen/Qwen3-14B-FP8z Qwen3 14BzQwen/Qwen3-Embedding-8BzQwen3 Embedding 8Bz$Qwen/Qwen3-VL-235B-A22B-Instruct-FP8zQwen3 VL 235B A22B Instructz"Qwen/Qwen3-VL-30B-A3B-Instruct-FP8zQwen3 VL 30B A3B InstructzQwen/Qwen3.5-35B-A3B-FP8zQwen3.5 35B A3BzQwen/Qwen3.5-397B-A17BzQwen3.5 397B A17Bz3.6zQwen/Qwen3.5-9Bz Qwen3.5 9BzQwen/Qwen3.6-35B-A3B-FP8zQwen3.6 35B A3BzQwen/Qwen3.8-27B-FP8z[Realtime pricing. See https://docs.doubleword.ai/inference-api/models/qwen-qwen3-8-27b-fp8.zdeepseek-ai/DeepSeek-V4-FlashziRealtime pricing. See https://docs.doubleword.ai/inference-api/models/deepseek-ai-deepseek-v4-flash-0731.z0.18zdeepseek-ai/DeepSeek-V4.1-FlashzDeepSeek V4.1 FlashzfRealtime pricing. See https://docs.doubleword.ai/inference-api/models/deepseek-ai-deepseek-v4-1-flash.z0.01zgoogle/gemma-4-31B-itzGemma 4 31B ITz'mistralai/Devstral-2-123B-Instruct-2512zDevstral 2 123B Instruct 2512izYRealtime pricing. See https://docs.doubleword.ai/inference-api/models/moonshotai-kimi-k3.z.nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4zNemotron 3 Super 120B A12Bzopenai/gpt-oss-20bz GPT OSS 20Bzzai-org/GLM-5.1-FP8zGLM 5.1zzai-org/GLM-5.2-FP8zZRealtime pricing. See https://docs.doubleword.ai/inference-api/models/zai-org-glm-5-2-fp8.z0.93)r2r4rUrVr?rYrZ fireworks Fireworkszhttps://api\.fireworks\.aizhttps://fireworks.ai/pricingzaccounts/fireworks/z*accounts/fireworks/models/deepseek-r1-0528zDeepSeek R1 0528aJThe updated DeepSeek-R1-0528 model delivers major improvements in reasoning, inference, and accuracy through enhanced post-training optimization and greater computational resources. It now performs at a level approaching top-tier models like O3 and Gemini 2.5 Pro, with notable gains in complex tasks such as math and programming.iqzdeepseek-v3-0324z*accounts/fireworks/models/deepseek-v3-0324zDeepseek V3 03-24zA strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token from Deepseek. Updated checkpoint.zUdocs give just one price - "Pricing Per 1M Tokens", we assume that's input and outputz0.9z deepseek-v3p2z'accounts/fireworks/models/deepseek-v3p2z Deepseek V3.2zModel from Deepseek that harmonizes high computational efficiency with superior reasoning and agent performance. 675B parameter MoE model.z0.56z1.68z+accounts/fireworks/models/deepseek-v4-flashz0accounts/fireworks/models/deepseek-v4-flash-0731zDeepSeek-V4-FlashzbOfficial release of DeepSeek-V4-Flash with enhanced agentic capabilities and speculative decoding.izNStandard serverless pricing. See https://docs.fireworks.ai/serverless/pricing.z)accounts/fireworks/models/deepseek-v4-prozDeepSeek-V4-Prozgemma-3-27b-itz(accounts/fireworks/models/gemma-3-27b-itzGemma 3 27B Instructizglm-4p7z!accounts/fireworks/models/glm-4p7zNext-generation general-purpose model from Z.ai optimized for coding, reasoning, and agentic workflows. 352B parameter MoE model with advanced thinking controls.izglm-5p1z!accounts/fireworks/models/glm-5p1z glm-5p1-fastz'accounts/fireworks/routers/glm-5p1-fastz GLM 5.1 FastzJFast serverless pricing. See https://docs.fireworks.ai/serverless/pricing.z2.8z0.52zglm-5p2z!accounts/fireworks/models/glm-5p2aGLM-5.2 introduces a robust 1M-token context and advanced, multi-effort coding capabilities to significantly enhance performance on long-horizon tasks. Features a new IndexShare architecture and improved MTP layer for greater efficiency. 743B parameter MoE model from Z.ai.z glm-5p2-fastz'accounts/fireworks/routers/glm-5p2-fastz*accounts/fireworks/routers/glm-5p2-fast-uszVFast and US-only serverless pricing. See https://docs.fireworks.ai/serverless/pricing.z&accounts/fireworks/models/gpt-oss-120bzOpenAI gpt-oss-120bzOpenAI's open-weight 117B parameter MoE model designed for production, general purpose, high reasoning use-cases. Features powerful reasoning, agentic tasks, and versatile developer use cases.zTStandard serverless pricing. See https://fireworks.ai/models/fireworks/gpt-oss-120b.z%accounts/fireworks/models/gpt-oss-20bzOpenAI gpt-oss-20bzOpenAI's open-weight 21.5B parameter model designed for powerful reasoning, agentic tasks, and versatile developer use cases. Optimized for lower latency and local or specialized tasks.zSStandard serverless pricing. 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The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.zllama4-maverick-instruct-basicz8accounts/fireworks/models/llama4-maverick-instruct-basicz!Llama 4 Maverick Instruct (Basic)z minimax-m2p1z&accounts/fireworks/models/minimax-m2p1z MiniMax-M2.1zBuilt for strong real-world performance across complex, multi-language, and agent-driven workflows. 228B parameter model with robust support for systems, backend, web, mobile, and office-style tasks.i z minimax-m2p7z&accounts/fireworks/models/minimax-m2p7z MiniMax M2.7z minimax-m3z$accounts/fireworks/models/minimax-m3z MiniMax M3zMultimodal foundation model from MiniMax with text, image, and video inputs, a long context window, and long-horizon agentic work.iznemotron-3-ultra-nvfp4z0accounts/fireworks/models/nemotron-3-ultra-nvfp4zNVIDIA Nemotron 3 Ultra NVFP4aFrontier-scale LLM from NVIDIA using a hybrid Latent Mixture-of-Experts (LatentMoE) architecture with interleaved Mamba-2 and MoE layers plus select Attention layers. 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Every response also carries a `copilot_usage.token_details[].cost_per_batch` figure in nano-credits, which agreed with the published rate for each of the nine priced models reachable on the plan used to check them on 2026-09-03. Long-context tiers reprice the whole request once the prompt crosses the threshold. Not represented: embedding models and Copilot-internal agent models, which have no published rate, and `gpt-4`, which Copilot routes to GPT-4.1 and bills at a rate the pricing page does not list. Catalog membership varies by subscription and by API integrator, so this is not the union of every plan's models.copiloti@zYThe pricing page gives cached input as a $0.25-$1.00 range; the highest rate is recorded.zclaude-fable-5.1i2zclaude-opus-4.8-fastzClaude Opus 4.8 (fast mode)z6Fast mode is priced at 2x the standard Opus 4.8 rates.zgemini-3.5-flashzGemini 3.5 Flashz>Copilot does not charge for cache writes on the Gemini models.9zgemini-3.6-flashzGemini 3.6 Flashzgemini-3.7-flashzGemini 3.7 Flashzgemini-3.8-flashzGemini 3.8 Flashi@ z gpt-3.5-turbozgpt-3.5-turbo-0613z GPT 3.5 TurbozzIncluded in the subscription: the pricing page lists no rate, and a live request reported a zero token cost on 2026-09-03.zgpt-4.1zgpt-4.1-2025-04-14zGPT-4.1zgpt-4ozgpt-4o-2024-05-13zgpt-4o-2024-08-06zgpt-4o-2024-11-20zgpt-4-o-previewzGPT-4oz gpt-4o-minizgpt-4o-mini-2024-07-18z GPT-4o miniz gpt-5-miniz^gpt-5-mini-\d{4}-\d{2}-\d{2}$z GPT-5 miniz0.025z gpt-5.3-codexz"^gpt-5\.3-codex-\d{4}-\d{2}-\d{2}$z GPT-5.3-Codexiz1.75z0.17514zgpt-5.4z^gpt-5\.4-\d{4}-\d{2}-\d{2}$zAPrompts over 272,000 tokens are billed at the long-context rates.i&z gpt-5.4-miniz!^gpt-5\.4-mini-\d{4}-\d{2}-\d{2}$z GPT-5.4 minizgpt-5.5z^gpt-5\.5-\d{4}-\d{2}-\d{2}$z!^gpt-5\.6-luna-\d{4}-\d{2}-\d{2}$z GPT-5.6 Lunai@zAPrompts over 200,000 tokens are billed at the long-context rates.z ^gpt-5\.6-sol-\d{4}-\d{2}-\d{2}$z GPT-5.6 Solz"^gpt-5\.6-terra-\d{4}-\d{2}-\d{2}$z GPT-5.6 Terrazkimi-k2.7-codezmai-code-1-flash-pickerzMAI-Code-1-FlashzVThe catalog id carries a `-picker` suffix; the pricing page names it MAI-Code-1-Flash.zmai-code-1.1-flashzMAI-Code-1.1-FlashgoogleGooglezhttps://(.*\.)?googleapis\.comz-https://ai.google.dev/gemini-api/docs/pricingz8https://cloud.google.com/vertex-ai/generative-ai/pricinggeminivertex usageMetadatapromptTokenCountcachedContentTokenCountcacheTokensDetailsz array-matchmodalityTEXT)typefieldr3 tokenCountAUDIOIMAGEDOCUMENTVIDEOcache_video_read_tokenspromptTokensDetailsinput_video_tokenscandidatesTokensDetailsoutput_image_tokensoutput_video_tokenscandidatesTokenCountthoughtsTokenCounttoolUsePromptTokenCountinput_tool_tokenstoolUsePromptTokensDetailsinput_text_tool_tokensinput_audio_tool_tokensinput_image_tool_tokensinput_video_tool_tokens modelVersionzclaude-opus-4@zanthropic/claude-sonnet-4zclaude-fable-5@zwFlat pricing across full 1M context window. Ref: https://cloud.google.com/vertex-ai/generative-ai/pricing#claude-modelszclaude-fable-5-1@arFlat pricing across full 1M context window. Global endpoint; regional and multi-region endpoints add a 10% premium. Cache hits are 0.025x base input (not the usual 0.1x), unique to Fable 5.1 and Mythos 5.1. Ref: https://cloud.google.com/vertex-ai/generative-ai/pricing#claude-models Model ID ref: https://platform.claude.com/docs/en/build-with-claude/claude-on-vertex-aizclaude-opus-5@zGlobal endpoint pricing, flat across the full 1M context window. Multi-region and regional endpoints carry a 10% premium. Ref: https://cloud.google.com/vertex-ai/generative-ai/pricing#claude-modelszclaude-opus-5-5@acGlobal endpoint pricing, flat across the full 1M context window. Multi-region and regional endpoints carry a 10% premium. Google's pricing page renders client-side and could not be read when this entry was added; the rates follow Anthropic's list price, as every other Claude entry in this file does. Cache hits are 0.05x base input (not the usual 0.1x), unique to Opus 5.5. Ref: https://cloud.google.com/vertex-ai/generative-ai/pricing#claude-models Anthropic ref: https://platform.claude.com/docs/en/about-claude/pricing#model-pricing Model ID ref: https://platform.claude.com/docs/en/models/opus-5-5/overviewz~Long-context rates apply above 200K input tokens. Ref: https://cloud.google.com/vertex-ai/generative-ai/pricing#partner-modelsz|Flat pricing across the full 1M context window. Ref: https://cloud.google.com/vertex-ai/generative-ai/pricing#partner-modelszgemini-1.0-pro-vision-001zgemini 1.0 pro visionzGoogle's first-generation advanced multimodal model that can understand text, code, and images. It provides strong reasoning capabilities and follows instructions effectively.zWI can't find anything about this model or it's pricing, so trusting the original sourcez0.125z0.375zgemini-1.5-flashzgemini 1.5 flashzA faster, more cost-effective variant of Gemini 1.5 that maintains strong capabilities while optimizing for performance and cost efficiency. Suitable for production deployments requiring high throughput.z0.01875zgemini-1.5-prozgemini 1.5 ProzGoogle's most capable multimodal model with an extremely long context window of up to 1 million tokens. It excels at complex reasoning, long-form content processing, and multimodal understanding.zgemini-2.0-flashzgemini-2.0-flash-0zgemini-2.0-flash-expzgemini-2.0-flash-thinkingzgemini-2.0-flash-latestzgemini 2.0 flashzThe newest generation of Google's Gemini models, featuring improved reasoning, instruction following, and factual accuracy, with the Flash variant optimized for cost-efficiency and performance.)r0r<r1rhcache_audio_read_mtokzgemini-2.0-flash-litezgemini 2.0 flash litezA lighter, more cost-effective version of Gemini 2.0 Flash, designed for applications requiring high efficiency while maintaining good performance. Ideal for high-volume, cost-sensitive deployments.zgemini-2.5-flashzgemini-2.5-flash-latestz gemini-2.5-flash-preview-09-2025zGemini 2.5 FlashaGemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling.zgemini-2.5-flash-imagezgemini-2.5-flash-image-previewzGemini 2.5 Flash ImagezGoogle's specialized image generation model optimized for fast, high-quality image generation. Outputs images at 1024x1024 resolution, with each image consuming 1290 output tokens.aNSee https://ai.google.dev/gemini-api/docs/pricing#gemini-2.5-flash-image. Image output is priced at $30 per 1M tokens, with each 1024x1024 image = 1290 tokens = $0.039/image. Cache pricing is not available for this model. Text output uses the Gemini 2.5 Flash $2.50 rate and is the aggregate remainder when modality details omit text.)r0r1output_image_mtokzgemini-2.5-flash-litezgemini-2.5-flash-lite-previewz^(?!.*-[tT][tT][sS](?:$|-)))and_zGemini 2.5 Flash LiteaGemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance across common benchmarks compared to earlier Flash models. By default, "thinking" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.z!gemini-2.5-flash-lite-preview-ttsz!Gemini 2.5 Flash-Lite Preview TTSz?See https://cloud.google.com/text-to-speech/pricing#gemini-tts.zgemini-2.5-flash-previewzgemini-2.5-flash-preview-05-20zgemini-2.5-flash-preview-04-17z'gemini-2.5-flash-preview-05-20:thinkingz!gemini-2.5-flash-preview:thinkingzGemini 2.5 Flash Preview 05-20a.Gemini 2.5 Flash May 20th Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater accuracy and nuanced context handling.zZfrom https://cloud.google.com/vertex-ai/generative-ai/pricing should be retired 2025-07-15)r2r3r4r5r?r`r7zgemini-2.5-flash-ttszgemini-2.5-flash-preview-ttszGemini 2.5 Flash TTSzgemini-2.5-prozGemini 2.5 ProaGemini 2.5 Pro is Google's state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs "thinking" capabilities, enabling it to reason through responses with enhanced accuracy and nuanced context handling. Gemini 2.5 Pro achieves top-tier performance on multiple benchmarks, including first-place positioning on the LMArena leaderboard, reflecting superior human-preference alignment and complex problem-solving abilities.z@See https://ai.google.dev/gemini-api/docs/pricing#gemini-2.5-pro)r2r3r4r5r?r7zgemini-2.5-pro-ttszgemini-2.5-pro-preview-ttszGemini 2.5 Pro TTSzgemini-3-flash-previewzgemini-3-flash-preview-zGemini 3 Flash PreviewzGoogle's ultra-fast frontier model optimized for speed and efficiency. Delivers state-of-the-art performance while maintaining low latency and cost, with improved reasoning and coding capabilities.zySee https://ai.google.dev/gemini-api/docs/pricing. Standard pricing shown; Batch API offers 50% discount on input/output.zgemini-3-pro-image-previewzgemini-3-pro-imagezGemini 3 Pro Image PreviewzGoogle's image generation model optimized for high-quality image generation. Supports 1K/2K and 4K resolution outputs with flexible pricing based on image dimensions.aCSee https://ai.google.dev/gemini-api/docs/pricing#gemini-3-pro-image. Image output is priced at $120 per 1M tokens, with each 1K/2K image = 1120 tokens = $0.134/image and each 4K image = 2000 tokens = $0.24/image. Text and thinking output is $12 per 1M tokens and is the aggregate remainder when modality details omit text.120zgemini-3-pro-previewzgemini-3-pro-text-previewzGemini 3 Pro PreviewzrThe best model in the world for multimodal understanding, and our most powerful agentic and vibe-coding model yet.zgemini-3.1-flash-image-previewzgemini-3.1-flash-imagezGemini 3.1 Flash Image PreviewzGoogle's latest image generation model (Nano Banana 2) optimized for fast, high-quality image generation. Supports multiple output resolutions from 512px to 4K, with text and thinking output priced separately from image output tokens.zSee https://ai.google.dev/gemini-api/docs/pricing. Text and thinking output is priced at $3 per 1M tokens and is the aggregate remainder when modality details omit text. Image output is priced at $60 per 1M tokens. Preview model - pricing may change.zgemini-3.1-flash-litezgemini-3.1-flash-lite-previewzGemini 3.1 Flash LitezGoogle's fastest and most cost-efficient Gemini 3 series model, built for intelligence at scale. Optimized for high-volume, low-latency applications while maintaining strong multimodal capabilities.z2See https://ai.google.dev/gemini-api/docs/pricing.zgemini-3.1-flash-lite-imagezGemini 3.1 Flash Lite ImagezHGoogle's low-latency, cost-efficient image generation and editing model.zNSee https://ai.google.dev/gemini-api/docs/pricing#gemini-3.1-flash-lite-image.zgemini-3.1-flash-live-previewzGemini 3.1 Flash Live PreviewzHGoogle's low-latency audio-to-audio model with multimodal input support.zPSee https://ai.google.dev/gemini-api/docs/pricing#gemini-3.1-flash-live-preview.)r0r1rhriinput_image_mtokinput_video_mtokzgemini-3.1-pro-previewzGemini 3.1 Pro PreviewzThe latest performance, intelligence, and usability improvements to the best model family in the world for multimodal understanding, agentic capabilities, and vibe-coding.zgemini-3.5-flash-previewz^gemini-3\.5-flash-\dzGoogle's most intelligent model built for speed, combining frontier intelligence with improved reasoning, coding, and multimodal understanding.zSee https://ai.google.dev/gemini-api/docs/pricing. Standard tier pricing shown; Batch and Flex tiers offer 50% discount on input/output.zgemini-3.5-flash-litezGemini 3.5 Flash LitezGoogle's fastest and most cost-efficient Gemini 3.5 series model, optimized for high-volume, low-latency applications while maintaining strong multimodal capabilities.zSee https://ai.google.dev/gemini-api/docs/pricing. Standard tier pricing shown; Batch and Flex tiers offer 50% discount. Input rate is unified across text/image/video/audio (no separate audio rate).aBSee https://ai.google.dev/gemini-api/docs/pricing. Standard tier pricing shown; Batch and Flex tiers offer 50% discount. No separate audio input rate documented. Introductory rates apply through 2026-12-31. The cache storage price ($0.50 per 1M tokens per hour) has no unit in prices/units.yml and is not represented here.izGoogle's most capable Flash model, built for complex coding, web development, agentic workflows and reliable multi-step execution.a0See https://ai.google.dev/gemini-api/docs/pricing. Standard tier pricing shown; Batch and Flex tiers offer 50% discount, Priority tier is 1.8x. Introductory rates apply through 2026-12-31. The cache storage price ($0.50 per 1M tokens per hour) has no unit in prices/units.yml and is not represented here.zGoogle's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows.zgemini-embedding-001zgemini-embedding-2zGemini Embedding 2zRGoogle's multimodal embedding model for text, images, audio, video, and documents.zESee https://ai.google.dev/gemini-api/docs/pricing#gemini-embedding-2.z6.5)r0rhrrzgemini-flash-1.5zGemini 1.5 Flasha8Gemini 1.5 Flash is a foundation model that performs well at a variety of multimodal tasks such as visual understanding, classification, summarization, and creating content from image, audio and video. It's adept at processing visual and text inputs such as photographs, documents, infographics, and screenshots.zBSee https://ai.google.dev/gemini-api/docs/pricing#gemini-1.5-flashzgemini-flash-1.5-8bzESee https://ai.google.dev/gemini-api/docs/pricing#gemini-1.5-flash-8bzgemini-live-2.5-flashz%gemini-2.5-flash-native-audio-previewz$gemini-2.5-flash-native-audio-latestzGemini Live 2.5 FlashaGoogle's Live API model for low-latency bidirectional voice and video interactions, GA on Vertex AI (model id `gemini-live-2.5-flash`, served from the `global` location). The prefix match also covers the AI Studio preview ids (`gemini-live-2.5-flash-preview*`).zSee https://cloud.google.com/vertex-ai/generative-ai/pricing (Live API) and https://ai.google.dev/gemini-api/docs/pricing - GA pricing matches the preview.zgemini-omni-flash-previewzGemini Omni Flash PreviewzBGoogle's video generation and editing model with multimodal input.zLSee https://ai.google.dev/gemini-api/docs/pricing#gemini-omni-flash-preview.z17.5)r0r1output_video_mtokz gemini-prozgemini-1.0-prozgemini 1.0 prozOI can't find anything so trusting these prices, not sure the model still existszgemini-pro-1.5zGemini 1.5 ProzVGoogle's latest multimodal model, supports image and video[0] in text or chat prompts.iz@See https://ai.google.dev/gemini-api/docs/pricing#gemini-1.5-proz0.3125zgemma-2-27b-itz Gemma 2 27BzGemma 2 27B by Google is an open model built from the same research and technology used to create the Gemini models. Gemma models are well-suited for a variety of text generation and instruction-following tasks.zeImported from OpenRouter pricing; verify against Google pricing when native API pricing is published.zgemma-3zgemma-3-zGemma 3 (free)zgLightweight, state-of the art, open model built from the same technology that powers our Gemini models.zgemma-3nzGemma 3n (free)zlOur open model built for efficient performance on everyday devices like mobile phones, laptops, and tablets.zgemma-4-26b-a4b-itzGemma 4 26B A4BzGemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference.a!Gemini API model ID. Free of charge on the Gemini API with no paid tier, see https://ai.google.dev/gemini-api/docs/pricing. The Vertex AI Model-as-a-Service offering uses the gemma-4-26b-a4b-it-maas ID and is priced separately. The previous rates were imported from OpenRouter, not Google.zgemma-4-26b-a4b-it-maasz Gemma 4 26B A4B (Vertex AI MaaS)zPGemma 4 26B A4B IT served by Vertex AI as a managed Model-as-a-Service endpoint.zVertex AI Model-as-a-Service rates, see https://cloud.google.com/vertex-ai/generative-ai/pricing. Model ID from https://cloud.google.com/vertex-ai/generative-ai/docs/maas/use-open-models.zgemma-4-31b-itzGemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. It features a 256K token context window, configurable thinking/reasoning mode, and native function calling.aUFree of charge on the Gemini API with no paid tier, see https://ai.google.dev/gemini-api/docs/pricing. Not offered as Model-as-a-Service on Vertex AI (only Gemma 4 26B is); there it is self-deployed from Model Garden and billed as endpoint compute, so no per-token price applies. The previous rates were imported from OpenRouter, not Google.) r2r4rUrVrWrXrYrrZgroqGroqzhttps://api\.groq\.comz$https://console.groq.com/docs/modelszdeepseek-r1-distill-llama-70bzDeepSeek R1 Distill Llama 70Bz gemma-7b-itz gemma2-9b-itz gemma2-9bz Gemma 2 9B 8kzllama-3.1-405b-reasoningz0.59z0.79zllama-3.1-70b-versatilezllama-3.1-8b-instantzLlama 3.1 8B Instant 128kzllama-3.2-11b-text-previewzllama-3.2-11b-vision-previewzllama-3.2-1b-previewzllama-3.2-3b-previewzllama-3.2-90b-text-previewzllama-3.2-90b-vision-previewzllama-3.3-70b-specdeczllama-3.3-70b-versatilezLlama 3.3 70B Versatile 128kzllama-guard-3-8bzllama2-70b-4096zllama3-70b-8192zllama3-8b-8192z%llama3-groq-70b-8192-tool-use-previewz0.89z$llama3-groq-8b-8192-tool-use-previewz-meta-llama/llama-4-maverick-17b-128e-instructzLlama 4 Maverick 17B 128Ez)meta-llama/llama-4-scout-17b-16e-instructzLlama 4 Scout (17Bx16E) 128kz0.34zmeta-llama/llama-guard-4-12bzLlama Guard 4 12Bzmistral-saba-24bzmixtral-8x7b-32768zmoonshotai/kimi-k2-instructz moonshotai/kimi-k2-instruct-0905zKimi K2 1T 128kzopenai/gpt-oss-safeguard-20bzGPT-OSS 120B is OpenAI's flagship open source model, built on a Mixture-of-Experts (MoE) architecture with 120 billion parameters and 128 experts. )r2r3r5r6r7zGPT-OSS 20B is OpenAI's flagship open source model, built on a Mixture-of-Experts (MoE) architecture with 20 billion parameters and 32 experts. zqwen/qwen3-32bzQwen3 32B 131kzwhisper-large-v3zWhisper Large V3z9See https://console.groq.com/docs/model/whisper-large-v3.z0.111) audio_hoursinput_audio_hourszwhisper-large-v3-turbozWhisper Large V3 Turboz?See https://console.groq.com/docs/model/whisper-large-v3-turbo.)r2r4rUrVrYrZhuggingface_cerebraszHuggingFace (cerebras)z(https://router\.huggingface\.co/cerebrasz'https://router.huggingface.co/v1/modelsz'https://huggingface.co/inference/models huggingfacez meta-llama/Llama-3.1-8B-Instructz 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Achieves top performance in real-world engineering, office productivity, and character-rich interaction.zMiniMax-M2.7-highspeedzM2.7-highspeedzm2.7-highspeedzMiniMax M2.7 Highspeedz6MiniMax M2.7 highspeed variant with higher throughput.z MiniMax-01zbMiniMax-01 combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding.iCzfImported from OpenRouter pricing; verify against MiniMax pricing when native API pricing is published.z minimax-m1z MiniMax M1aMiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing efficient long-context processing.zMiniMax-M3 is a multimodal foundation model from MiniMax. 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It is optimized for reasoning and supports a wide multilingual range, including over 20 languages.zministral-14b-2512zMinistral 3 14B 2512zThe largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart.z ministral-3bz Ministral 3BaYMinistral 3B is a 3B parameter model optimized for on-device and edge computing. It excels in knowledge, commonsense reasoning, and function-calling, outperforming larger models like Mistral 7B on most benchmarks. 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Read the launch announcement here.zmistral-large-2512zMistral Large 3 2512zMistral Large 3 2512 is Mistral's most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.zmistral-medium-2312zMistral Medium 1zBMistral's first enterprise-grade model, released in December 2023.aRetired on 2025-06-16; retained for historical usage records at its original $2.70/$8.10 per MTok rates. Ref: https://github.com/mistralai/platform-docs-public/blob/222f4ba9114f84ce9f2d718b9a12fbac1e527f4b/src/schema/models/models/mistral-medium-1-0-23-12.tsz2.7z8.1zmistral-medium-3-1zmistral-mediumzmistral-medium-2505zmistral-medium-2508zMistral Medium 3 and 3.1uwMistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. 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