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
534
个提供方
75
最近同步
2026年8月31日
534 个模型
openai logoopenai

OpenAI: o3

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....

上下文
200K
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image · text · file
输出
text
输入: $2.00输出: $8.00每百万 Token
查看模型详情
openai logoopenai

OpenAI: o4 Mini

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...

上下文
200K
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image · text · file
输出
text
输入: $1.10输出: $4.40每百万 Token
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openai logoopenai

OpenAI: GPT-4.1

GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...

上下文
1.0M
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image · text · file
输出
text
输入: $2.00输出: $8.00每百万 Token
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openai logoopenai

OpenAI: GPT-4.1 Mini

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...

上下文
1.0M
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image · text · file
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text
输入: $0.400输出: $1.60每百万 Token
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openai logoopenai

OpenAI: GPT-4.1 Nano

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...

上下文
1.0M
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image · text · file
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text
输入: $0.100输出: $0.400每百万 Token
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meta-llama logometa-llama

Meta: Llama 4 Maverick

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...

上下文
1.0M
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text · image
输出
text
输入: $0.200输出: $0.696每百万 Token
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meta-llama logometa-llama

Meta: Llama 4 Scout

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

上下文
1.3M
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text · image
输出
text
输入: $0.110输出: $0.340每百万 Token
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deepseek logodeepseek

DeepSeek: DeepSeek V3 0324

DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the DeepSeek V3 model and performs really well...

上下文
164K
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text
输出
text
输入: $0.250输出: $1.00每百万 Token
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openai logoopenai

OpenAI: o1-pro

The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...

上下文
200K
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text · image · file
输出
text
输入: $150.00输出: $600.00每百万 Token
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mistralai logomistralai

Mistral: Mistral Small 3.1 24B

Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and...

上下文
128K
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text · image
输出
text
输入: $0.351输出: $0.555每百万 Token
查看模型详情
google logogoogle

Google: Gemma 3 4B

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

上下文
131K
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text · image
输出
text
输入: $0.050输出: $0.100每百万 Token
查看模型详情
google logogoogle

Google: Gemma 3 12B

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

上下文
131K
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text · image
输出
text
输入: $0.050输出: $0.150每百万 Token
查看模型详情
cohere logocohere

Cohere: Command A

Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases. Compared to other leading proprietary...

上下文
256K
输入
text
输出
text
输入: $2.50输出: $10.00每百万 Token
查看模型详情
rekaai logorekaai

Reka Flash 3

Reka Flash 3 is a general-purpose, instruction-tuned large language model with 21 billion parameters, developed by Reka. It excels at general chat, coding tasks, instruction-following, and function calling. Featuring a...

上下文
66K
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text
输出
text
输入: $0.100输出: $0.200每百万 Token
查看模型详情
google logogoogle

Google: Gemma 3 27B

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

上下文
131K
输入
text · image
输出
text
输入: $0.080输出: $0.450每百万 Token
查看模型详情
thedrummer logothedrummer

TheDrummer: Skyfall 36B V2

Skyfall 36B v2 is an enhanced iteration of Mistral Small 2501, specifically fine-tuned for improved creativity, nuanced writing, role-playing, and coherent storytelling.

上下文
33K
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text
输出
text
输入: $0.550输出: $0.800每百万 Token
查看模型详情
perplexity logoperplexity

Perplexity: Sonar Reasoning Pro

Note: Sonar Pro pricing includes Perplexity search pricing. See details here Sonar Reasoning Pro is a premier reasoning model powered by DeepSeek R1 with Chain of Thought (CoT). Designed for...

上下文
128K
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text · image
输出
text
输入: $2.00输出: $8.00每百万 Token
查看模型详情
perplexity logoperplexity

Perplexity: Sonar Pro

Note: Sonar Pro pricing includes Perplexity search pricing. See details here For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibility, like...

上下文
200K
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text · image
输出
text
输入: $3.00输出: $15.00每百万 Token
查看模型详情
perplexity logoperplexity

Perplexity: Sonar Deep Research

Sonar Deep Research is a research-focused model designed for multi-step retrieval, synthesis, and reasoning across complex topics. It autonomously searches, reads, and evaluates sources, refining its approach as it gathers...

上下文
128K
输入
text
输出
text
输入: $2.00输出: $8.00每百万 Token
查看模型详情
mistralai logomistralai

Mistral: Saba

Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional...

上下文
33K
输入
text · file
输出
text
输入: $0.200输出: $0.600每百万 Token
查看模型详情
openai logoopenai

OpenAI: o3 Mini High

OpenAI o3-mini-high is the same model as o3-mini with reasoningeffort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...

上下文
200K
输入
text · file
输出
text
输入: $1.10输出: $4.40每百万 Token
查看模型详情
aion-labs logoaion-labs

AionLabs: Aion-RP 1.0 (8B)

Aion-RP-Llama-3.1-8B ranks the highest in the character evaluation portion of the RPBench-Auto benchmark, a roleplaying-specific variant of Arena-Hard-Auto, where LLMs evaluate each other’s responses. It is a fine-tuned base model...

上下文
33K
输入
text
输出
text
输入: $0.800输出: $1.60每百万 Token
查看模型详情
qwen logoqwen

Qwen: Qwen2.5 VL 72B Instruct

Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

上下文
128K
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text · image
输出
text
输入: $0.250输出: $0.750每百万 Token
查看模型详情
qwen logoqwen

Qwen: Qwen-Plus

Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.

上下文
1M
输入
text
输出
text
输入: $0.260输出: $0.780每百万 Token
查看模型详情