Models
Browse all models configured in Meteor and filter them by capabilities, context length and pricing.
77 models
Claude 3.5 Haiku - Fast and efficient
Max context: 200K tokensPrompt: $1.0000/1M tokensOutput: $5.0000/1M tokens
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anthropicclaudefastefficient
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Claude 3.7 Sonnet - Hybrid AI reasoning
Max context: 200K tokensPrompt: $3.0000/1M tokensOutput: $15.0000/1M tokens
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anthropicclaudehybridreasoning
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Claude 3 Haiku - Legacy fast model
Max context: 200K tokensPrompt: $1.0000/1M tokensOutput: $5.0000/1M tokens
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anthropicclaudelegacyfast
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Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance across reasoning, coding, and computer-use tasks, Haiku 4.5 brings frontier-level capability to real-time and high-volume applications.
It introduces extended thinking to the Haiku line; enabling controllable reasoning depth, summarized or interleaved thought output, and tool-assisted workflows with full support for coding, bash, web search, and computer-use tools. Scoring >73% on SWE-bench Verified, Haiku 4.5 ranks among the world’s best coding models while maintaining exceptional responsiveness for sub-agents, parallelized execution, and scaled deployment.
Max context: 200K tokensPrompt: $1.0000/1M tokensOutput: $5.0000/1M tokens
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Claude
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Claude Haiku 4.5 (October 1, 2025 version) is Anthropic's fastest and most cost-effective hybrid reasoning model, featuring extended thinking chain capabilities. It approaches Sonnet 4's performance in coding, agent tasks, and multimodal processing (such as text + images), but with over 2x speed improvements and only 1/3 the cost. It supports a 200K token context window (approximately 150K English words), integrates computer use, tool calling, and context-aware features, and is suitable for low-latency scenarios like customer service agents, real-time chat, and multi-agent subtasks. Compared to Haiku 3.5, it significantly outperforms on SWE-bench Verified (73.3%) and MMMU (visual reasoning) benchmarks, making it the ideal choice for budget-sensitive production environments and free-tier products.
Max context: 200K tokensPrompt: $1.0000/1M tokensOutput: $5.0000/1M tokens
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Claude Opus 4.1 (dated) - Specific version
Max context: 200K tokensPrompt: $3.0000/1M tokensOutput: $15.0000/1M tokens
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anthropicclaudeagenticversioned
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No description provided for this model
Max context: 200K tokensPrompt: $15.0000/1M tokensOutput: $75.0000/1M tokens
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No tags configured
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Claude Opus 4.5 - Most intelligent model for complex tasks
Max context: 200K tokensPrompt: $5.0000/1M tokensOutput: $25.0000/1M tokens
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anthropicclaudeintelligentcodingagents
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Claude Opus 4.5 (November 1, 2025 version) is Anthropic's most advanced hybrid reasoning model, featuring breakthrough chain-of-thought capabilities. It excels in coding, content generation, data analysis, and planning, supports a 200K token context window (approximately 150K English words), and integrates image understanding and computer use functions, making it suitable for complex multi-step tasks and visual reasoning. Compared to previous models, it leads on graduate-level reasoning (GPQA) and undergraduate knowledge (MMLU) benchmarks, with 2x faster reasoning speed, making it the ideal choice for daily productivity and professional development.
Max context: 200K tokensPrompt: $5.0000/1M tokensOutput: $25.0000/1M tokens
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No tags configured
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Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%), Sonnet 4 balances capability and computational efficiency, making it suitable for a broad range of applications from routine coding tasks to complex software development projects. Key enhancements include improved autonomous codebase navigation, reduced error rates in agent-driven workflows, and increased reliability in following intricate instructions. Sonnet 4 is optimized for practical everyday use, providing advanced reasoning capabilities while maintaining efficiency and responsiveness in diverse internal and external scenarios.
Read more at the blog post here
Max context: 1.0M tokensPrompt: $3.0000/1M tokensOutput: $15.0000/1M tokens
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Claude
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Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with improvements across system design, code security, and specification adherence. The model is designed for extended autonomous operation, maintaining task continuity across sessions and providing fact-based progress tracking.
Sonnet 4.5 also introduces stronger agentic capabilities, including improved tool orchestration, speculative parallel execution, and more efficient context and memory management. With enhanced context tracking and awareness of token usage across tool calls, it is particularly well-suited for multi-context and long-running workflows. Use cases span software engineering, cybersecurity, financial analysis, research agents, and other domains requiring sustained reasoning and tool use.
Max context: 1.0M tokensPrompt: $3.0000/1M tokensOutput: $15.0000/1M tokens
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Claude
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Claude Sonnet 4.5 (September 29, 2025 version) is Anthropic's powerful and versatile hybrid reasoning model, supporting extended thinking chain and interleaved tool use. It leads globally in coding, agent tasks, and computer operations, supports a 200K token context window (approximately 150K English words, 1M preview version), integrates visual reasoning, memory tools, and context editing features, and is suitable for long-duration autonomous work such as software development, multi-agent systems, and financial analysis. Compared to Sonnet 4, it shows significant improvements on SWE-bench Verified (77.2%) and GPQA Diamond (83.4%) benchmarks, balances speed and cost, is the top choice for developer agents and enterprise productivity, and offers the best safety alignment (reducing deception and sycophancy behaviors).
Max context: 200K tokensPrompt: $3.0000/1M tokensOutput: $15.0000/1M tokens
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gemini-2.0-flash
chatGoogle Gemini 2.0 Flash - Default model (Jan 2025)
Max context: 1.0M tokensPrompt: $0.3750/1M tokensOutput: $1.5000/1M tokens
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googlegeminidefaultfast
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Gemini 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.
Additionally, Gemini 2.5 Flash is configurable through the "max tokens for reasoning" parameter,
Max context: 1.0M tokensPrompt: $0.3000/1M tokensOutput: $2.5000/1M tokens
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Gemini
Audio pricing: Prompt $1.0000/1M tokens · Output —
Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation, edits, and multi-turn conversations.
Max context: 33K tokensPrompt: $0.0390/per request
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Gemini
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Gemini 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
Max context: 1.0M tokensPrompt: $0.1000/1M tokensOutput: $0.4000/1M tokens
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Gemini
Audio pricing: Prompt $0.3000/1M tokens · Output —
Gemini 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.
Max context: 1.0M tokensPrompt: $0.1000/1M tokensOutput: $0.4000/1M tokens
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Gemini
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Gemini 2.5 Flash is a high-performance generative AI model developed by Google DeepMind, belonging to the "Flash" variant of the Gemini 2.5 series. Designed as a "workhorse" model, it focuses on fast and excellent performance for everyday tasks, providing timely and low-latency responses. Thanks to Google's wake-up support for the "Think" (think) function in Flash models, it allows developers to dynamically control the model's inference process to balance speed, cost, and accuracy.
Max context: 1.0M tokensPrompt: $0.1500/1M tokensOutput: $8.3400/1M tokens
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Gemini 2.5 Flash Preview September 2025 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.
Max context: 1.0M tokensPrompt: $0.3000/1M tokensOutput: $2.5000/1M tokens
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Gemini
Audio pricing: Prompt — · Output $1.0000/1M tokens
Our 2.5 Flash text-to-speech audio model has been optimized to achieve cost-effective, low-latency, and controllable speech generation.
Max context: 4K tokensPrompt: $0.5000/1M tokensOutput: $10.0000/1M tokens
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Gemini 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.
Max context: 1.0M tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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Gemini
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Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and high-fidelity visual synthesis. The model generates context-rich graphics, from infographics and diagrams to cinematic composites, and can incorporate real-time information via Search grounding.
It offers industry-leading text rendering in images (including long passages and multilingual layouts), consistent multi-image blending, and accurate identity preservation across up to five subjects. Nano Banana Pro adds fine-grained creative controls such as localized edits, lighting and focus adjustments, camera transformations, and support for 2K/4K outputs and flexible aspect ratios. It is designed for professional-grade design, product visualization, storyboarding, and complex multi-element compositions while remaining efficient for general image creation workflows.
Max context: 66K tokensPrompt: $0.1400/per request
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Gemini
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Gemini 3 Pro is Google’s flagship frontier model for high-precision multimodal reasoning, combining strong performance across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling,
It delivers state-of-the-art benchmark results in general reasoning, STEM problem solving, factual QA, and multimodal understanding, including leading scores on LMArena, GPQA Diamond, MathArena Apex, MMMU-Pro, and Video-MMMU. Interactions emphasize depth and interpretability: the model is designed to infer intent with minimal prompting and produce direct, insight-focused responses.
Built for advanced development and agentic workflows, Gemini 3 Pro provides robust tool-calling, long-horizon planning stability, and strong zero-shot generation for complex UI, visualization, and coding tasks. It excels at agentic coding (SWE-Bench Verified, Terminal-Bench 2.0), multimodal analysis, and structured long-form tasks such as research synthesis, planning, and interactive learning experiences. Suitable applications include autonomous agents, coding assistants, multimodal analytics, scientific reasoning, and high-context information processing.
Max context: 1.0M tokensPrompt: $2.0000/1M tokensOutput: $12.0000/1M tokens
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Gemini
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GPT-4.1 是一款针对高级指令遵循、实际软件工程以及长语境推理进行优化的大型语言模型。它支持 100 万个标记的上下文窗口，并在编码（54.6% 的 SWE-bench 验证分数）、指令遵循（87.4% 的 IFEval）以及多模态理解基准测试中优于 GPT-4o 和 GPT-4.5。它针对精确的代码差异、代理可靠性以及大型文档环境中的高召回率进行了优化，因此非常适合用于代理、集成开发环境工具和企业知识检索。
Max context: 1.0M tokensPrompt: $2.0000/1M tokensOutput: $8.0000/1M tokens
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GPT
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GPT-4.1 是一款针对高级指令遵循、实际软件工程以及长语境推理进行优化的大型语言模型。它支持 100 万个标记的上下文窗口，并在编码（54.6% 的 SWE-bench 验证分数）、指令遵循（87.4% 的 IFEval）以及多模态理解基准测试中优于 GPT-4o 和 GPT-4.5。它针对精确的代码差异、代理可靠性以及大型文档环境中的高召回率进行了优化，因此非常适合用于代理、集成开发环境工具和企业知识检索。
Max context: 1.0M tokensPrompt: $2.0000/1M tokensOutput: $8.0000/1M tokens
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GPT
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GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard instruction evals, 35.8% on MultiChallenge, and 84.1% on IFEval. Mini also shows strong coding ability (e.g., 31.6% on Aider’s polyglot diff benchmark) and vision understanding, making it suitable for interactive applications with tight performance constraints.
Max context: 1.0M tokensPrompt: $0.4000/1M tokensOutput: $1.6000/1M tokens
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GPT
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GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard instruction evals, 35.8% on MultiChallenge, and 84.1% on IFEval. Mini also shows strong coding ability (e.g., 31.6% on Aider’s polyglot diff benchmark) and vision understanding, making it suitable for interactive applications with tight performance constraints.
Max context: 1.0M tokensPrompt: $0.4000/1M tokensOutput: $1.6000/1M tokens
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GPT
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For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million token context window, and scores 80.1% on MMLU, 50.3% on GPQA, and 9.8% on Aider polyglot coding – even higher than GPT‑4o mini. It’s ideal for tasks like classification or autocompletion.
Max context: 1.0M tokensPrompt: $0.1000/1M tokensOutput: $0.4000/1M tokens
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GPT
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For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million token context window, and scores 80.1% on MMLU, 50.3% on GPQA, and 9.8% on Aider polyglot coding – even higher than GPT‑4o mini. It’s ideal for tasks like classification or autocompletion.
Max context: 1.0M tokensPrompt: $0.1000/1M tokensOutput: $0.4000/1M tokens
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GPT
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GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of GPT-4 Turbo while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.
For benchmarking against other models, it was briefly called "im-also-a-good-gpt2-chatbot"
#multimodal
Max context: 128K tokensPrompt: $2.5000/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of GPT-4 Turbo while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.
For benchmarking against other models, it was briefly called "im-also-a-good-gpt2-chatbot"
#multimodal
Max context: 128K tokensPrompt: $2.5000/1M tokensOutput: $10.0000/1M tokens
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GPT
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The 2024-08-06 version of GPT-4o offers improved performance in structured outputs, with the ability to supply a JSON schema in the respone_format.
Max context: 128K tokensPrompt: $2.5000/1M tokensOutput: $10.0000/1M tokens
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GPT
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The 2024-11-20 version of GPT-4o offers a leveled-up creative writing ability with more natural, engaging, and tailored writing to improve relevance & readability. It’s also better at working with uploaded files, providing deeper insights & more thorough responses.
Max context: 128K tokensPrompt: $2.5000/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs.
As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.
GPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences common leaderboards.
Check out the launch announcement to learn more.
#multimodal
Max context: 128K tokensPrompt: $0.1500/1M tokensOutput: $0.6000/1M tokens
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GPT
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GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs.
As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.
GPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences common leaderboards.
Check out the launch announcement to learn more.
#multimodal
Max context: 128K tokensPrompt: $0.1500/1M tokensOutput: $0.6000/1M tokens
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GPT
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GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs.
As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.
Max context: 128K tokensPrompt: $0.1500/1M tokensOutput: $0.6000/1M tokens
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GPT
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GPT-4o mini Transcribe is a speech-to-text model that uses GPT-4o mini to transcribe audio. It offers improvements to word error rate and better language recognition and accuracy compared to original Whisper models. Use it for more accurate transcripts.
Max context: 16K tokensPrompt: $1.2500/1M tokensOutput: $5.0000/1M tokens
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No tags configured
Audio pricing: Prompt $3.0000/1M tokens · Output —
OpenAI GPT-4o Mini TTS - Text to speech
Max context: 4K tokensPrompt: $0.6000/1M tokensOutput: $12.0000/1M tokens
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openaittsvoice
Audio pricing: Prompt $0.6000/1M tokens · Output $12.0000/1M tokens
GPT-4o Transcribe is a speech-to-text model that uses GPT-4o to transcribe audio. It offers improvements to word error rate and better language recognition and accuracy compared to original Whisper models. Use it for more accurate transcripts.
Max context: 16K tokensPrompt: $2.5000/1M tokensOutput: $10.0000/1M tokens
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No tags configured
Audio pricing: Prompt $6.0000/1M tokens · Output —
GPT-4o Transcribe Diarize is an automatic speech recognition (ASR) model with built-in speaker diarization, meaning it associates audio segments with different speakers in a conversation. This model is only available in the Transcription API.
Max context: 16K tokensPrompt: $2.5000/1M tokensOutput: $10.0000/1M tokens
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No tags configured
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GPT-5 是 OpenAI 最先进的模型，其在推理能力、代码质量以及用户体验方面都有显著提升。该模型针对需要分步推理、遵循指令以及在高风险应用场景中保持高准确性的复杂任务进行了优化。它支持测试时的路由功能和高级的提示理解，包括用户指定的意图，例如“好好思考一下这个”。改进之处包括减少了幻觉、谄媚行为，并在编码、写作和健康相关任务中表现得更为出色。
Max context: 400K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5.1 Chat (AKA Instant is the fast, lightweight member of the 5.1 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on harder queries, improving accuracy on math, coding, and multi-step tasks without slowing down typical conversations. The model is warmer and more conversational by default, with better instruction following and more stable short-form reasoning. GPT-5.1 Chat is designed for high-throughput, interactive workloads where responsiveness and consistency matter more than deep deliberation.
Max context: 128K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5.1 Chat (AKA Instant is the fast, lightweight member of the 5.1 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on harder queries, improving accuracy on math, coding, and multi-step tasks without slowing down typical conversations. The model is warmer and more conversational by default, with better instruction following and more stable short-form reasoning. GPT-5.1 Chat is designed for high-throughput, interactive workloads where responsiveness and consistency matter more than deep deliberation.
Max context: 128K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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No description provided for this model
Max context: 128K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT-5-Codex is a specialized version of GPT-5 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks. The model supports building projects from scratch, feature development, debugging, large-scale refactoring, and code review. Compared to GPT-5, Codex is more steerable, adheres closely to developer instructions, and produces cleaner, higher-quality code outputs. Reasoning effort can be adjusted with the reasoning.effort parameter. Read the docs here
Codex integrates into developer environments including the CLI, IDE extensions, GitHub, and cloud tasks. It adapts reasoning effort dynamically—providing fast responses for small tasks while sustaining extended multi-hour runs for large projects. The model is trained to perform structured code reviews, catching critical flaws by reasoning over dependencies and validating behavior against tests. It also supports multimodal inputs such as images or screenshots for UI development and integrates tool use for search, dependency installation, and environment setup. Codex is intended specifically for agentic coding applications.
Max context: 400K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost. GPT-5 Mini is the successor to OpenAI's o4-mini model.
Max context: 400K tokensPrompt: $0.2500/1M tokensOutput: $2.0000/1M tokens
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GPT
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GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost. GPT-5 Mini is the successor to OpenAI's o4-mini model.
Max context: 400K tokensPrompt: $0.2500/1M tokensOutput: $2.0000/1M tokens
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GPT
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GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger counterparts, it retains key instruction-following and safety features. It is the successor to GPT-4.1-nano and offers a lightweight option for cost-sensitive or real-time applications.
Max context: 400K tokensPrompt: $0.0500/1M tokensOutput: $0.4000/1M tokens
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GPT
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GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger counterparts, it retains key instruction-following and safety features. It is the successor to GPT-4.1-nano and offers a lightweight option for cost-sensitive or real-time applications.
Max context: 400K tokensPrompt: $0.0500/1M tokensOutput: $0.4000/1M tokens
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GPT
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GPT-5 Pro is OpenAI’s most advanced model, offering major improvements in reasoning, code quality, and user experience. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy in high-stakes use cases. It supports test-time routing features and advanced prompt understanding, including user-specified intent like "think hard about this." Improvements include reductions in hallucination, sycophancy, and better performance in coding, writing, and health-related tasks.
Max context: 400K tokensPrompt: $15.0000/1M tokensOutput: $120.0000/1M tokens
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GPT
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GPT-5.1 is the latest frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, improved instruction adherence, and a more natural conversational style compared to GPT-5. It uses adaptive reasoning to allocate computation dynamically, responding quickly to simple queries while spending more depth on complex tasks. The model produces clearer, more grounded explanations with reduced jargon, making it easier to follow even on technical or multi-step problems.
Built for broad task coverage, GPT-5.1 delivers consistent gains across math, coding, and structured analysis workloads, with more coherent long-form answers and improved tool-use reliability. It also features refined conversational alignment, enabling warmer, more intuitive responses without compromising precision. GPT-5.1 serves as the primary full-capability successor to GPT-5
Max context: 400K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5.1 Chat 模型（又名“即时版”，是 5.1 系列中一款快速、轻量且高效的成员，专为低延迟聊天而优化，同时保留了强大的通用智能。它采用自适应推理技术，对较难的问题进行有选择性的“思考”，从而在数学、编程和多步骤任务方面提高准确性，同时不会影响正常的对话速度。该模型默认情况下更亲切、更具对话性，具有更好的指令响应能力和更稳定的简短推理能力。GPT-5.1 会话模型专为高吞吐量、交互性工作负载而设计，在响应速度和一致性方面比深度思考更为重要。）
Max context: 128K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5.1 Chat 模型（又名“即时版”，是 5.1 系列中一款快速、轻量且高效的成员，专为低延迟聊天而优化，同时保留了强大的通用智能。它采用自适应推理技术，对较难的问题进行有选择性的“思考”，从而在数学、编程和多步骤任务方面提高准确性，同时不会影响正常的对话速度。该模型默认情况下更亲切、更具对话性，具有更好的指令响应能力和更稳定的简短推理能力。GPT-5.1 会话模型专为高吞吐量、交互性工作负载而设计，在响应速度和一致性方面比深度思考更为重要。）
Max context: 128K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5.1 Chat points to the GPT-5.1 snapshot currently used in ChatGPT. We recommend GPT-5.1 for most API usage, but feel free to use this GPT-5.1 Chat model to test our latest improvements for chat use cases.
Max context: 128K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT-5.1-Codex is a specialized version of GPT-5.1 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks. The model supports building projects from scratch, feature development, debugging, large-scale refactoring, and code review. Compared to GPT-5.1, Codex is more steerable, adheres closely to developer instructions, and produces cleaner, higher-quality code outputs. Reasoning effort can be adjusted with the reasoning.effort parameter.
Codex integrates into developer environments including the CLI, IDE extensions, GitHub, and cloud tasks. It adapts reasoning effort dynamically—providing fast responses for small tasks while sustaining extended multi-hour runs for large projects. The model is trained to perform structured code reviews, catching critical flaws by reasoning over dependencies and validating behavior against tests. It also supports multimodal inputs such as images or screenshots for UI development and integrates tool use for search, dependency installation, and environment setup. Codex is intended specifically for agentic coding applications.
Max context: 2.6M tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5.1-Codex-Max is a specialized large-language model (LLM) optimized for agentic coding tasks—that is, software engineering workflows that involve planning, multi-step reasoning, iteration, refactoring, testing, and working across multiple files and sessions.
It builds on the GPT-5.1 / Codex lineage, designed not just for “code autocomplete” but for sustained, project-scale code work.
Max context: 400K tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-5.1-Codex is a specialized version of GPT-5.1 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks. The model supports building projects from scratch, feature development, debugging, large-scale refactoring, and code review. Compared to GPT-5.1, Codex is more steerable, adheres closely to developer instructions, and produces cleaner, higher-quality code outputs. Reasoning effort can be adjusted with the reasoning.effort parameter.
Codex integrates into developer environments including the CLI, IDE extensions, GitHub, and cloud tasks. It adapts reasoning effort dynamically—providing fast responses for small tasks while sustaining extended multi-hour runs for large projects. The model is trained to perform structured code reviews, catching critical flaws by reasoning over dependencies and validating behavior against tests. It also supports multimodal inputs such as images or screenshots for UI development and integrates tool use for search, dependency installation, and environment setup. Codex is intended specifically for agentic coding applications.
Max context: 2.6M tokensPrompt: $1.2500/1M tokensOutput: $10.0000/1M tokens
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GPT
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GPT-Image-1 是 OpenAI 推出的最新图像生成模型，结合了语言理解与图像生成能力，能够生成高质量、照片级真实感的图像。它在指令理解、世界知识、细节表现和多功能性方面表现出色，适用于从文本生成图像、图像编辑到参考图像生成等多种场景。
Max context: 0 tokensPrompt: $10.0000/1M tokensOutput: $40.0000/1M tokens
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GPT
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GPT-Image-1 是 OpenAI 推出的最新图像生成模型，结合了语言理解与图像生成能力，能够生成高质量、照片级真实感的图像。它在指令理解、世界知识、细节表现和多功能性方面表现出色，适用于从文本生成图像、图像编辑到参考图像生成等多种场景。
Max context: 0 tokensPrompt: $2.5000/1M tokensOutput: $8.0000/1M tokens
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GPT
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Grok 3 is the latest model from xAI. It's their flagship model that excels at enterprise use cases like data extraction, coding, and text summarization. Possesses deep domain knowledge in finance, healthcare, law, and science.
Max context: 131K tokensPrompt: $3.0000/1M tokensOutput: $15.0000/1M tokens
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Grok
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A lightweight model that thinks before responding. Fast, smart, and great for logic-based tasks that do not require deep domain knowledge. The raw thinking traces are accessible.
Max context: 131K tokensPrompt: $0.3000/1M tokensOutput: $0.5000/1M tokens
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Grok
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Grok 4 is xAI's latest reasoning model with a 256k context window. It supports parallel tool calling, structured outputs, and both image and text inputs. Note that reasoning is not exposed, reasoning cannot be disabled, and the reasoning effort cannot be specified. Pricing increases once the total tokens in a given request is greater than 128k tokens. See more details on the xAI docs
Max context: 4K tokensPrompt: $3.0000/1M tokensOutput: $15.0000/1M tokens
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Grok
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Grok 4 Fast is xAI's latest multimodal model with SOTA cost-efficiency and a 2M token context window. It comes in two flavors: non-reasoning and reasoning. Read more about the model on xAI's news post.
Reasoning can be enabled/disabled using the reasoning enabled parameter in the API. Learn more in our docs
Max context: 2.0M tokensPrompt: $0.2000/1M tokensOutput: $0.5000/1M tokens
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Grok
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Grok 4 Fast is xAI's latest multimodal model with SOTA cost-efficiency and a 2M token context window. It comes in two flavors: non-reasoning and reasoning. Read more about the model on xAI's news post.
Reasoning can be enabled/disabled using the reasoning enabled parameter in the API. Learn more in our docs
Max context: 2.0M tokensPrompt: $0.2000/1M tokensOutput: $0.5000/1M tokens
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Grok
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o1-2024-12-17
chatOpenAI o1 - Advanced reasoning model
Max context: 128K tokensPrompt: $15.0000/1M tokensOutput: $60.0000/1M tokens
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openaireasoningadvanced
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o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.
Max context: 200K tokensPrompt: $2.0000/1M tokensOutput: $8.0000/1M tokens
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GPT
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OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding.
This model supports the reasoning_effort parameter, which can be set to "high", "medium", or "low" to control the thinking time of the model. The default is "medium". OpenRouter also offers the model slug openai/o3-mini-high to default the parameter to "high".
The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities.
The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.
Max context: 200K tokensPrompt: $1.1000/1M tokensOutput: $4.4000/1M tokens
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GPT
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o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.
Max context: 200K tokensPrompt: $2.0000/1M tokensOutput: $8.0000/1M tokens
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GPT
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OpenAI o3-mini-high is the same model as o3-mini with reasoning_effort set to high.
o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities.
The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.
Max context: 200K tokensPrompt: $1.1000/1M tokensOutput: $4.4000/1M tokens
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GPT
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The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o3-pro model uses more compute to think harder and provide consistently better answers.
Note that BYOK is required for this model. Set up here: https://openrouter.ai/settings/integrations
Max context: 200K tokensPrompt: $20.0000/1M tokensOutput: $80.0000/1M tokens
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GPT
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OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains.
Despite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.
Max context: 200K tokensPrompt: $1.1000/1M tokensOutput: $4.4000/1M tokens
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GPT
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OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains.
Despite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.
Max context: 200K tokensPrompt: $1.1000/1M tokensOutput: $4.4000/1M tokens
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GPT
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Sora 2 is OpenAI's latest video and audio generation model, capable of directly outputting movie-level realistic videos based on text prompts. It features complete audio-visual capabilities such as multi-camera narrative, environmental and physical simulation, and synchronized sound effects. Users can also inject their own appearance and voice into characters through selfies or voice recordings, enabling "everyone to act in movies". In terms of real-world simulation, Sora 2 can precisely reproduce natural phenomena such as water, fabric, and gravity by following the laws of object movement, material properties, light and shadow, and dynamics, making character and camera movements highly credible.
Max context: -1 tokensPrompt: $0.2000/per request
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Sora
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Sora-image is OpenAI's latest image generation and editing model, capable of directly outputting high-fidelity, art-level static images based on text prompts. It has a complete visual generation capability, including multi-style narrative composition, precise light and shadow and texture simulation, as well as controllable detail editing functions. Users can also upload selfies or other pictures to embed their own images into the generated scenes or creatively transform existing photos, making "everyone an artist" a reality.
Max context: -1 tokensPrompt: $0.0400/per request
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text-embedding-3-large is OpenAI's most capable embedding model for both english and non-english tasks. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.
Max context: 8K tokensPrompt: $0.1300/per request
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GPT
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text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.
Max context: 8K tokensPrompt: $0.0200/per request
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GPT
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text-embedding-ada-002 is OpenAI's legacy text embedding model.
Max context: 8K tokensPrompt: $0.1000/per request
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GPT
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