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OpenRouterで現在公開されているすべてのモデルを検索し、モダリティ、コンテキスト、料金、設定、プロバイダー情報を比較できます。
- カタログ範囲
- 公開モデルすべて
- モデル
- 534
- プロバイダー
- 75
- 最終同期
- 2026/08/31
openaiOpenAI: 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....
- コンテキスト
- 200K
- 入力
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- 出力
- text
openaiOpenAI: 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...
- コンテキスト
- 200K
- 入力
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- 出力
- text
openaiOpenAI: 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...
- コンテキスト
- 1.0M
- 入力
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- 出力
- text
openaiOpenAI: 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...
- コンテキスト
- 1.0M
- 入力
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openaiOpenAI: 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...
- コンテキスト
- 1.0M
- 入力
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- 出力
- text
meta-llamaMeta: 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...
- コンテキスト
- 1.0M
- 入力
- text · image
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- text
meta-llamaMeta: 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...
- コンテキスト
- 1.3M
- 入力
- text · image
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deepseekDeepSeek: 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...
- コンテキスト
- 164K
- 入力
- text
- 出力
- text
openaiOpenAI: 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...
- コンテキスト
- 200K
- 入力
- text · image · file
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mistralaiMistral: 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...
- コンテキスト
- 128K
- 入力
- text · image
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googleGoogle: 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,...
- コンテキスト
- 131K
- 入力
- text · image
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googleGoogle: 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,...
- コンテキスト
- 131K
- 入力
- text · image
- 出力
- text
cohereCohere: 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...
- コンテキスト
- 256K
- 入力
- text
- 出力
- text
rekaaiReka 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...
- コンテキスト
- 66K
- 入力
- text
- 出力
- text
googleGoogle: 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,...
- コンテキスト
- 131K
- 入力
- text · image
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- text
thedrummerTheDrummer: 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.
- コンテキスト
- 33K
- 入力
- text
- 出力
- text
perplexityPerplexity: 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...
- コンテキスト
- 128K
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perplexityPerplexity: 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...
- コンテキスト
- 200K
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perplexityPerplexity: 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...
- コンテキスト
- 128K
- 入力
- text
- 出力
- text
mistralaiMistral: 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...
- コンテキスト
- 33K
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- text · file
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openaiOpenAI: 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...
- コンテキスト
- 200K
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aion-labsAionLabs: 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...
- コンテキスト
- 33K
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- text
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qwenQwen: 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.
- コンテキスト
- 128K
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qwenQwen: Qwen-Plus
Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.
- コンテキスト
- 1M
- 入力
- text
- 出力
- text