模型雷达 · OPENROUTER

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
631
个提供方
86
最近同步
2026年9月29日
631 个模型
openai logoopenai

OpenAI: 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
输入: $0.15输出: $0.6每百万 Token
查看模型详情 →
openai logoopenai

OpenAI: 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
输入: $0.0296输出: $0.136每百万 Token
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openai logoopenai

OpenAI: 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
输入: $0.018输出: $0.09每百万 Token
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openai logoopenai

OpenAI: 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
输入: $0.024输出: $0.112每百万 Token
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anthropic logoanthropic

Anthropic: 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
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image · text · file
输出
text
输入: $15输出: $75每百万 Token
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anthropic logoanthropic

Anthropic: 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
输入: $7.5输出: $37.5每百万 Token
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mistralai logomistralai

Mistral: 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
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text · file
输出
text
输入: $0.3输出: $0.9每百万 Token
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mistralai logomistralai

Mistral: Codestral 2508 (batch)

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
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text · file
输出
text
输入: $0.15输出: $0.45每百万 Token
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qwen logoqwen

Qwen: 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
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text
输出
text
输入: $0.07输出: $0.28每百万 Token
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qwen logoqwen

Qwen: 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
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text
输出
text
输入: $0.0481输出: $0.193每百万 Token
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z-ai logoz-ai

Z.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
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text
输出
text
输入: $0.6输出: $2.2每百万 Token
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z-ai logoz-ai

Z.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
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text
输出
text
输入: $0.13输出: $0.85每百万 Token
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qwen logoqwen

Qwen: 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
131K
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text
输出
text
输入: $0.23输出: $2.3每百万 Token
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qwen logoqwen

Qwen: 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
输入: $0.3输出: $1每百万 Token
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bytedance logobytedance

ByteDance: 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
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image · text
输出
text
输入: $0.1输出: $0.2每百万 Token
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google logogoogle

Google: 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
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text · image · file · audio · video
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text
输入: $0.1输出: $0.4每百万 Token
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google logogoogle

Google: Gemini 2.5 Flash Lite (batch)

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
输入: $0.05输出: $0.2每百万 Token
查看模型详情 →
qwen logoqwen

Qwen: Qwen3 235B A22B Instruct 2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...

上下文
262K
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text
输出
text
输入: $0.0875输出: $0.35每百万 Token
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moonshotai logomoonshotai

MoonshotAI: Kimi K2 0711

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...

上下文
131K
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text
输出
text
输入: $0.57输出: $2.3每百万 Token
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cognitivecomputations logocognitivecomputations

Venice: Uncensored

Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving...

上下文
128K
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text
输出
text
输入: $0.2输出: $0.9每百万 Token
查看模型详情 →
tencent logotencent

Tencent: Hunyuan A13B Instruct

Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark...

上下文
131K
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text
输出
text
输入: $0.14输出: $0.57每百万 Token
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morph logomorph

Morph: Morph V3 Large

Morph's high-accuracy apply model for complex code edits. 4,500 tokens/sec with 98% accuracy for precise code transformations. The model requires the prompt to be in the following format: <instruction>{instruction}</instruction> <code>{initialcode}</code>...

上下文
262K
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text
输出
text
输入: $0.9输出: $1.9每百万 Token
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morph logomorph

Morph: Morph V3 Fast

Morph's fastest apply model for code edits. 10,500 tokens/sec with 96% accuracy for rapid code transformations. The model requires the prompt to be in the following format: <instruction>{instruction}</instruction> <code>{initialcode}</code> <update>{editsnippet}</update>...

上下文
82K
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text
输出
text
输入: $0.8输出: $1.2每百万 Token
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baidu logobaidu

Baidu: ERNIE 4.5 VL 424B A47B

ERNIE-4.5-VL-424B-A47B is a multimodal Mixture-of-Experts (MoE) model from Baidu’s ERNIE 4.5 series, featuring 424B total parameters with 47B active per token. It is trained jointly on text and image data...

上下文
123K
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image · text
输出
text
输入: $0.42输出: $1.25每百万 Token
查看模型详情 →