AI 模型雷达
把 AI 模型放在一起比较
收录 OpenRouter 当前公开的全部模型，统一呈现模态、上下文窗口、价格、配置与提供方信息，并持续增量更新。
- 目录范围
- 全部公开
- 个模型
- 691
- 个提供方
- 98
- 最近同步
- 2026年10月30日
deepseekDeepSeek: DeepSeek V3.1
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...
- 上下文
- 164K
- 输入
- text
- 输出
- text
mistralaiMistral: Mistral Medium 3.1
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
- 上下文
- 131K
- 输入
- text · image · file
- 输出
- text
z-aiZ.ai: GLM 4.5V
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...
- 上下文
- 66K
- 输入
- text · image
- 输出
- text
openaiOpenAI: GPT-5
GPT-5 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...
- 上下文
- 400K
- 输入
- text · image · file
- 输出
- text
openaiOpenAI: GPT-5 (batch)
GPT-5 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...
- 上下文
- 400K
- 输入
- text · image · file
- 输出
- text
openaiOpenAI: GPT-5 Mini
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....
- 上下文
- 400K
- 输入
- text · image · file
- 输出
- text
openaiOpenAI: GPT-5 Mini (batch)
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....
- 上下文
- 400K
- 输入
- text · image · file
- 输出
- text
openaiOpenAI: GPT-5 Nano
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...
- 上下文
- 400K
- 输入
- text · image · file
- 输出
- text
openaiOpenAI: GPT-5 Nano (batch)
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...
- 上下文
- 400K
- 输入
- text · image · file
- 输出
- text
openaiOpenAI: gpt-oss-120b
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
- 上下文
- 131K
- 输入
- text
- 输出
- text
openaiOpenAI: gpt-oss-120b (batch)
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
- 上下文
- 131K
- 输入
- text
- 输出
- text
openaiOpenAI: gpt-oss-20b
gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
- 上下文
- 131K
- 输入
- text
- 输出
- text
openaiOpenAI: gpt-oss-20b (batch)
gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...
- 上下文
- 131K
- 输入
- text
- 输出
- text
anthropicAnthropic: Claude Opus 4.1
Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...
- 上下文
- 200K
- 输入
- image · text · file
- 输出
- text
anthropicAnthropic: Claude Opus 4.1 (batch)
Claude Opus 4.1 is an updated version of Anthropic’s flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains...
- 上下文
- 200K
- 输入
- image · text · file
- 输出
- text
mistralaiMistral: Codestral 2508
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. Blog Post
- 上下文
- 256K
- 输入
- text · file
- 输出
- text
qwenQwen: Qwen3 Coder 30B A3B Instruct
Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...
- 上下文
- 262K
- 输入
- text
- 输出
- text
qwenQwen: Qwen3 30B A3B Instruct 2507
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...
- 上下文
- 262K
- 输入
- text
- 输出
- text
z-aiZ.ai: GLM 4.5
GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly...
- 上下文
- 131K
- 输入
- text
- 输出
- text
z-aiZ.ai: GLM 4.5 Air
GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...
- 上下文
- 131K
- 输入
- text
- 输出
- text
qwenQwen: Qwen3 235B A22B Thinking 2507
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...
- 上下文
- 128K
- 输入
- text
- 输出
- text
qwenQwen: Qwen3 Coder 480B A35B
Qwen3-Coder-480B-A35B-Instruct is a Mixture-of-Experts (MoE) code generation model developed by the Qwen team. It is optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning over...
- 上下文
- 262K
- 输入
- text
- 输出
- text
bytedanceByteDance: UI-TARS 7B
UI-TARS-1.5 is a multimodal vision-language agent optimized for GUI-based environments, including desktop interfaces, web browsers, mobile systems, and games. Built by ByteDance, it builds upon the UI-TARS framework with reinforcement...
- 上下文
- 128K
- 输入
- image · text
- 输出
- text
googleGoogle: Gemini 2.5 Flash Lite
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...
- 上下文
- 1.0M
- 输入
- text · image · file · audio · video
- 输出
- text