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Claude Fable 5.1 is Anthropic's successor to Claude Fable 5 for long-running agentic coding, knowledge work and research. It has a 1M-token context window, 128K max output, tool use, and text, image and file input.

Claude Fable 5.2 is Anthropic's frontier model for the most demanding technical work, with gains over Fable 5.1 in coding, reasoning and vision. It supports text and image input, a 1M-token context window, 128K max output and always-on adaptive thinking.

Claude Fable 5 is Anthropic's Mythos-class model for autonomous knowledge work and coding. It has a 1M-token context window, 128K max output, tool use, and text, image and file input.

Claude Haiku 4.5 is Anthropic's fast Claude model for coding, with more than twice the speed of larger Claude models. It has 64,000 max output tokens, tool use, and text, image and file input.

Claude Haiku 5.5 is Anthropic's fastest model in the Claude 5.x lineup, built for rapid ideation, summarization and classification. It has vision input, tool use and always-on adaptive thinking.

Claude Opus 4.5 is Anthropic's frontier-class model for complex analysis, advanced coding and multi-step reasoning. It supports tool use, 64,000 max output tokens, and text, image and file input.

Claude Opus 4.6 is Anthropic's flagship-tier Claude 4 model for reasoning, advanced coding and nuanced analysis. It has 128K max output, tool use, and text, image and file input.

Claude Opus 4.7 is Anthropic's model for sophisticated research, advanced coding and multi-step agentic workflows. It has 128K max output, tool use, and text, image and file input.

Claude Opus 4.8 is Anthropic's most advanced Claude Opus model, built for complex reasoning, frontier-level coding and in-depth research. It has 128K max output and text, image and file input.

Claude Opus 5.5 is Anthropic's successor to Claude Opus 5 for long-running agentic coding and knowledge work. It has a 1M-token context window, vision input, tool use and always-on adaptive thinking, suited to multi-step changes in large codebases.

Claude Opus 5 is Anthropic's flagship model for demanding reasoning, coding and long-horizon agentic work. It handles end-to-end software tasks, code review, bug finding and chart analysis.

Claude Sonnet 4.5 is Anthropic's model that balances speed and intelligence for demanding text, coding and research tasks. It has 64,000 max output tokens, tool use, and text, image and file input.

Claude Sonnet 4.6 is Anthropic's balanced model for coding, analysis and reasoning. It supports tool use, up to 64,000 output tokens, and text, image and file input.

Claude Sonnet 4 is Anthropic's versatile model combining strong reasoning, coding and broad instruction following. It has a 1M-token context window, 64,000 max output tokens, tool use, and text, image and file input.

Claude Sonnet 5.5 is Anthropic's successor to Claude Sonnet 5 for well-scoped everyday work such as building features, fixing bugs, drafting and review. It has a 1M-token context window, 128K max output, vision input, tool use and adaptive thinking on by default.

Claude Sonnet 5 is Anthropic's agentic model with strong coding, tool use and reasoning. It has a 1M-token context window, 64,000 max output tokens, and takes text, image and file input.

DeepSeek-V4-Flash is DeepSeek's open-weight fast mixture-of-experts model for high-throughput chat and coding. It accepts text and image input and returns text. It supports reasoning, tool calling and agentic use.

DeepSeek V4 Pro is DeepSeek's open-weight high-capability reasoning model. It is a text model for chat and coding with streaming and function calling.

DeepSeek V4.1 Flash is the open-weight, cost-efficient sparse mixture-of-experts tier of the V4.1 family. It has 552B total parameters with 8B active on input and 16B on output, 1M context, and native vision in with text out. This is the original September 2026 checkpoint.

Gemini 3 Flash is Google's fast Gemini model with strong reasoning, coding, and multimodal understanding. It accepts text, image, video, and audio input. It supports tool calling.

Gemini 3.1 Pro is Google's most intelligent Gemini model, with improved reasoning and a medium thinking level. It takes text and image input. It supports tool calling and coding.

Gemini 3.5 Flash Lite is Google's high-throughput multimodal model for agentic workflows, complex coding, and long-horizon tasks. It has a 1M-token context window and accepts text and image input. It supports tool calling.

Gemini 3.5 Flash is Google's multimodal model for agentic workflows, complex coding, and long-horizon tasks. It takes text and image input and generates text. It supports tool calling and streaming.

Gemini 3.6 Flash is Google's frontier-level multimodal model that pairs fast inference with strong reasoning and coding. It accepts text and image input. It supports tool calling.

Gemini 3.7 Flash is Google's multimodal model for fast agentic workflows, coding, and complex multi-step reasoning. It accepts text, image, video, file, and audio input.

Gemini 3.8 Flash is Google's multimodal model for fast agentic workflows, coding, and complex multi-step reasoning. It has a 1,048,576-token context window. It accepts text, image, video, file, and audio input.

Gemini 4 Argon is Google's frontier model for long-horizon software engineering, enterprise knowledge work, and cybersecurity defense. It accepts text, image, and video input.

Gemini 4 Carbon is Google's strongest model, built for long-horizon agentic work such as multi-step coding and debugging. It reads text, images, and video and has a 1,048,576-token context window. It also targets knowledge work, research, and cybersecurity.

Gemini 4 Hydrogen is the speed and efficiency model of Google's Gemini 4 family, built for everyday coding and agentic workflows. It reads text, images, video, audio, and PDFs, answers in text, and has a 1,048,576-token context window with adjustable thinking levels.

Muse Ember is Meta's smallest and most efficient model in the Muse family, built for reasoning and everyday agent work. It has a 1M-token context window with up to 524,288 output tokens. It takes text, image, video, file and audio input and returns text.

Muse Spark 1.2 is Meta's multimodal reasoning model for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context window.

Muse Spark 1.3 is Meta's multimodal reasoning model for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and has a 1M-token context window. Audio understanding is not fully supported, so use Muse Spark 1.2 for audio.

Muse Wonder is Meta's frontier reasoning model for complex personal and professional agentic tasks, in preview. It accepts text, images, video, audio and PDF documents, returns text, and has a 1M-token context window.

MiniMax M2.5 is MiniMax's large language model for real-world productivity. It extends M2.1 coding expertise into office work such as generating Word, Excel and PowerPoint files. It scores 80.2% on SWE-Bench Verified and 76.3% on BrowseComp.

MiniMax M2.7 is MiniMax's large language model for complex software engineering, agentic tool use and office productivity workflows. It supports complex agent harnesses, dynamic tool search and Agent Teams. It takes text and supports function calling.

MiniMax M3 is MiniMax's multimodal language model for coding and agentic work. It accepts text, image and video input and returns text. It supports reasoning, function calling, structured output and multilingual use.

Mistral Large 4 is Mistral AI's open-weight Mixture-of-Experts model with about 1 trillion parameters and a 1M-token context. It takes text and image input and supports tool use, structured output and Low, Medium or High reasoning effort.

Kimi K2.5 is Moonshot AI's open-weight mixture-of-experts model with native vision, tool calling and structured outputs. It has 1T total and 32B active parameters, a 256K context window and a Modified MIT license.

Kimi K2.6 is Moonshot AI's open-weight large mixture-of-experts model with agentic tool use, vision input and long-context memory. It supports reasoning and streaming, and takes text and image input.

Kimi K2.7 Code is Moonshot AI's open-weight coding-focused model for end-to-end programming tasks over long contexts. It is a native multimodal mixture-of-experts model with 32B active of roughly 1T total parameters and always-on thinking.

Kimi K3 is Moonshot AI's open-weight multimodal reasoning model with native visual understanding. It accepts text, image and video input for long-horizon software engineering, knowledge work and CAD. Thinking is always on.

Nemotron 3.5 Super VL 120B A12B is NVIDIA's vision-language model for reasoning, coding and tool use. It is a hybrid Mamba-2 and Transformer mixture-of-experts with 120B total and 12B active parameters. It takes text, image and video input.

GPT-5 Codex is OpenAI's version of GPT-5 for agentic coding in Codex and similar environments. It has a 400,000-token input context and 128,000 output tokens, with text and image input. It supports reasoning tokens, streaming, function calling and structured outputs.

GPT-5 Nano is OpenAI's fastest GPT-5 model, built for summarization, classification and other simple high-volume tasks. It allows 128,000 output tokens. OpenAI recommends GPT-5.4 Nano for new workloads.

GPT-5.1 Codex Max is OpenAI's maximum-effort variant of GPT-5.1 Codex for long-horizon agentic coding in the Codex environment. It has extended context and reasoning support, accepts text and image input, and supports streaming and function calling.

GPT-5.1 Codex Mini is OpenAI's smaller version of GPT-5.1 Codex for agentic coding where efficiency matters more than peak capability. It has a 400,000-token input context and 128,000 output tokens, with text and image input. It supports function calling and reasoning tokens.

GPT-5.1 Codex is OpenAI's version of GPT-5.1 for agentic coding in the Codex environment. It has a 400,000-token input context and 128,000 output tokens, with text and image input. It supports reasoning tokens, streaming, function calling and structured outputs.

GPT-5.1 is OpenAI's flagship model for coding and agentic tasks, with configurable reasoning effort from none to high. It allows 128,000 output tokens and takes text and image input. It supports streaming, function calling and structured outputs.

GPT-5.2 Codex is OpenAI's Codex-environment variant of GPT-5.2, tuned for agentic coding workloads. It accepts text and image input and supports reasoning, streaming, function calling and structured outputs.

GPT-5.2 is OpenAI's previous-generation frontier model for professional work, with configurable reasoning effort. It allows 128,000 output tokens and takes text and image input. OpenAI recommends GPT-5.4 for new workloads.

GPT-5.3 Codex Spark is OpenAI's low-latency variant of GPT-5.3 Codex, tuned for fast iterative coding in the Codex environment. It is text-only and supports reasoning, streaming and function calling.

GPT-5.3 Codex is OpenAI's Codex-environment variant of GPT-5.3 for agentic coding. It accepts text and image input and supports reasoning, streaming, function calling and structured outputs.

GPT-5.4 Mini is OpenAI's mini model for coding, computer use and subagents, built for high-volume workloads. It allows 128,000 output tokens and takes text and image input. It supports reasoning tokens, function calling and structured outputs.

GPT-5.4 Nano is OpenAI's GPT-5.4-class model for simple, high-volume tasks such as classification, extraction and ranking. It allows 128,000 output tokens and takes text and image input. It supports function calling and structured outputs.

GPT-5.4 Pro is OpenAI's high-capacity model in the GPT-5 family, with advanced reasoning, broad knowledge and coding proficiency. It accepts text and image input and returns text, with tool-use capabilities.

GPT-5.4 is OpenAI's frontier model for complex professional workloads, with configurable reasoning effort from none to xhigh. It allows 128,000 output tokens and takes text and image input. It supports computer use, MCP and tool search.

GPT-5.5 Pro is OpenAI's Pro version of GPT-5.5, built for agentic workflows with built-in tools, improved reasoning and stateful context management. It accepts text and image input and supports coding, streaming and function calling.

GPT-5.5 is OpenAI's flagship model for coding, reasoning and multimodal work, with configurable reasoning effort from none to xhigh. It accepts text and image input. It supports streaming and function calling.

GPT-5.6 Luna is OpenAI's reasoning-focused model in the GPT-5.6 family, built for cost-sensitive workloads. It accepts text and image input. It supports streaming and function calling.

GPT-5.6 Sol is OpenAI's reasoning-focused model in the GPT-5.6 family, with configurable reasoning effort and image understanding. It accepts text, image and file input. It supports streaming and function calling.

GPT-5.6 Terra is OpenAI's reasoning-focused model in the GPT-5.6 family that balances intelligence and cost. It accepts text and image input. It supports streaming and function calling.

GPT-5 is OpenAI's previous flagship reasoning model, built for coding and agentic tasks with configurable reasoning effort. It allows 128,000 output tokens and takes text and image input. OpenAI recommends GPT-5.1 for new workloads.

GPT-6 Astra is OpenAI's reasoning and chat model. It accepts text and image input and supports streaming and function calling.

GPT-6 Luna is OpenAI's efficient GPT-6 tier for focused, high-throughput tasks. It has configurable reasoning, tool use, image input. It supports streaming and function calling.

GPT-6 Sol is OpenAI's model for complex coding and agentic workflows. It has configurable reasoning, tool use, image input. It is the high-end GPT-6 tier below GPT-6 Astra.

GPT-6.1 Sol is OpenAI's model for complex coding and agentic work, with performance close to GPT-6 Astra. It has configurable reasoning, tool use, and image input.

Qwen3.5 Plus is Alibaba's mid-tier "plus" model from the Qwen3.5 generation, with a 256K context window and strong reasoning, coding, and tool use.

Qwen3.6 Plus is Alibaba's plus-tier multimodal model of the Qwen3.6 generation. It takes text and image input, has a 1 million token context window, and supports reasoning, coding and tool use.

Qwen3.8 Flash is Alibaba Qwen's native vision-language model for coding, office work, long-context reasoning and agents. It has a 1M context window, takes text, image and video input, and supports thinking and function calling.

Qwen3.8 Max is Alibaba's flagship 2.4-trillion parameter MoE model of the Qwen3.8 generation. It takes text, image and video input, has a 1 million token context window, and supports reasoning, coding and tool use.

Frantic Ferret is an anonymous stealth preview multimodal chat model. It reads text, images, video, and PDF input and produces text, with reasoning, tool use, and structured output. The provider has not been publicly identified.

Grok 4.5 is SpaceXAI's model with frontier performance on coding, knowledge work, and STEM. It takes text and image input, returns text, and supports function calling and streaming.

Grok 4.6 is SpaceXAI's model with frontier performance on coding, knowledge work, and STEM. It builds on Grok 4.5 for long-running agents and visual work, with text and image input and function calling.

Grok 4.7 is SpaceXAI's frontier model for coding, agentic tasks, and knowledge work. It succeeds Grok 4.6 with mandatory adjustable reasoning at low, medium, high, or xhigh effort, defaulting to high. It takes text and image input.

Grok Build 0.1 is xAI's coding and automation model. It takes text and image input and supports function calling, structured outputs, and reasoning.

GLM-5.1 is Z-AI's open-weight flagship foundation model for long-horizon autonomous tasks. It has a 128K output window and scores 58.4 on SWE-Bench Pro. It supports thinking mode, function calling, and MCP integration.

GLM-5.2 is Z-AI's open-weight flagship reasoning model with a 128K output window. It supports controllable thinking effort, function calling, and MCP integration. It targets long-horizon autonomous coding and agentic tasks.

GLM-5.3 is Z.AI's open-weight reasoning model for coding and agentic workflows. It targets complex software engineering, long-running agents, and vulnerability analysis. It uses the same base model as GLM-5.2 with scaled post-training for stronger coding and token efficiency.

GLM-5 is Z-AI's open-weight general-purpose foundation model for reasoning, coding, and agentic workloads. It has a 128K context window and 32K output. It supports thinking mode, function calling, and structured outputs.