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LingDT-3.0-flash is Ant Digital Technologies' 124B-parameter Mixture-of-Experts model with about 5.1B active parameters per token. It targets token-efficient, production-scale agentic inference with function calling. Context window is 256,000 tokens.

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 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 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 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 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 V3.2 Exp is an experimental DeepSeek model built on V3.1-Terminus that adds DeepSeek Sparse Attention to improve long-context training and inference efficiency. It matches V3.1-Terminus on public benchmarks, and is released with open weights under the MIT license.

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 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash. It is an open-weight sparse mixture-of-experts model with native vision input, text output and a 1M-token context window.

Gemini 2.5 Flash-Lite is Google's lightest Gemini 2.5 Flash variant, built for high-throughput inference. It has a 1M-token context window and takes text, image, video, and audio input. It supports tool calling and coding.

Gemini 2.5 Flash is Google's fast Gemini model with strong reasoning, designed for high-throughput tasks. It takes text and image input and generates text. It supports tool calling and coding.

Gemini 2.5 Pro is Google's advanced Gemini model for deep reasoning over long context. It accepts text, image, video, and audio input and generates text. It fits complex research, coding, and analytical workflows.

Gemini 3.1 Flash Lite is Google's lightest Gemini model, built for high-throughput tasks. It takes text and image input and generates text. It supports tool calling, coding, and streaming responses.

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 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.

Ling-3.0-flash-Fin is inclusionAI's open-weight finance-focused mixture-of-experts model, built on Ling-3.0-flash with 124B total and 5.1B active parameters. It targets investment research, market analysis and financial reasoning. It keeps general reasoning and coding skills.

Ling-3.0-flash-Sante is inclusionAI's open-weight health and medicine mixture-of-experts model, built on Ling-3.0-flash with 124B total and 5.1B active parameters. It targets medical knowledge reasoning, clinical safety and evidence-based retrieval. It keeps coding skills.

Ling-3.0-flash-VL is inclusionAI's open-weight native multimodal mixture-of-experts model with 124B parameters and about 5.5B active per token. It adds image and video understanding. It suits visual reasoning, document and chart reading, and agentic GUI tasks.

Ling-3.1-flash is inclusionAI's open-weight hybrid reasoning mixture-of-experts model with 25B active parameters out of 560B total. It is a text model with streaming, function calling, coding and agentic use.

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.

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 K3.1 Pro Highspeed is Moonshot AI's high-speed variant of Kimi K3.1 Pro, running at about 2-3x the output speed. It has a 1M-token context window, native visual understanding and always-on thinking, and suits coding agents and latency-sensitive work.

Kimi K3.1 Pro is the first model in Moonshot AI's open-weight K3.1 series, a post-trained version of Kimi K3. It has a 1M-token context window and native visual understanding, and improves on K3 in coding, 3D and CAD modeling and financial research. Thinking is always on.

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.

GPT-4.1 Mini is OpenAI's smaller, faster version of GPT-4.1 with strong instruction following and tool calling. It has a 1,047,576-token input context and 32,768 output tokens. It takes text and image input and supports streaming, function calling and structured outputs.

GPT-4.1 Nano is OpenAI's fastest, most cost-efficient GPT-4.1 model, built for low-latency instruction following and tool calling at high volume. It has a 1,047,576-token input context and 32,768 output tokens, with text and image input.

GPT-4.1 is OpenAI's smartest non-reasoning model, built for instruction following and tool calling. It has a 1,047,576-token input context and 32,768 output tokens, and takes text and image input. It supports streaming, function calling and structured outputs.

GPT-4o Mini is OpenAI's fast, small multimodal model for focused tasks. It takes text and image input and returns text, with a 128,000-token input context and 16,384 output tokens. It supports streaming, function calling and structured outputs.

GPT-4o is OpenAI's versatile flagship multimodal model, with the o standing for omni. It takes text and image input and returns text, with a 128,000-token input context and 16,384 output tokens. It supports streaming, function calling and structured outputs.

GPT-5 Mini is OpenAI's reasoning model for low-latency, high-volume workloads. It allows 128,000 output tokens and takes text and image input. OpenAI recommends GPT-5.4 Mini for most new low-latency workloads.

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 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 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.

Qwen Flash is Alibaba Cloud's fast Qwen3-series text model on Model Studio, with thinking and non-thinking modes in one model. It supports a 1M token context window and tiered pricing by input length.

Qwen Plus is Alibaba Cloud's balanced general-purpose Qwen text model on Model Studio. It covers text understanding, generation and reasoning at a moderate price, with tiered pricing by input length.

Qwen3 Coder 480B A35B is Qwen's open-weight coding model with 480B total and 35B active parameters. It targets agentic coding, tool calling and repository-scale work, with a native 262K context window under Apache-2.0.

Qwen3 Coder Flash is the fast coding model of Alibaba's Qwen3-Coder family on Model Studio. It trades some depth for speed in code completion and agentic coding tools.

Qwen3 VL Plus is the higher-accuracy vision-language model of Alibaba's Qwen3-VL series on Model Studio. It reads images, charts and documents and answers in text, with a 256K token context window.

Qwen3.5-27B is Alibaba's largest open-weight dense Qwen3.5 model. It has a thinking mode, tool calling, multi-token prediction and 201 languages, with text, image and video input.

Qwen3.5 Flash is the fast, low-cost native vision-language model of Alibaba's Qwen3.5 series on Model Studio. It accepts text, image and video input and supports a 1M token context window.

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 Flash is the fast, low-cost native vision-language model of Alibaba's Qwen3.6 series on Model Studio. It improves on Qwen3.5 Flash in agentic coding, math and code reasoning, spatial understanding and object localization.

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.

Qwen3.7 Max is Alibaba's flagship max-tier model of the Qwen3.7 generation. It takes text and image input, has a 1 million token context window, and supports reasoning, coding and tool use.

Qwen3.7 Plus is Alibaba's advanced multimodal model with text and image input. It has a 1 million token context window and strong reasoning capabilities.

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.

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.