モデルレーダー · OPENROUTER
AIモデルを、同じ基準で比較。
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
- 631
- プロバイダー
- 86
- 最終同期
- 2026/09/29
openaiOpenAI: Text Embedding 3 Small (batch)
text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces...
- コンテキスト
- 8K
- 入力
- text
- 出力
- embeddings
perplexityPerplexity: Sonar Pro Search
Exclusively available on the OpenRouter API, Sonar Pro's new Pro Search mode is Perplexity's most advanced agentic search system. It is designed for deeper reasoning and analysis. Pricing is based...
- コンテキスト
- 200K
- 入力
- text · image
- 出力
- text
mistralaiMistral: Voxtral Small 24B 2507
Voxtral Small is an enhancement of Mistral Small 3, incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding. Input audio...
- コンテキスト
- 33K
- 入力
- text · audio · file
- 出力
- text
openaiOpenAI: gpt-oss-safeguard-20b
gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...
- コンテキスト
- 131K
- 入力
- text
- 出力
- text
qwenQwen: Qwen3 Embedding 8B
The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. This series inherits the exceptional multilingual capabilities, long-text...
- コンテキスト
- 33K
- 入力
- text
- 出力
- embeddings
qwenQwen: Qwen3 Embedding 4B
The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. This series inherits the exceptional multilingual capabilities, long-text...
- コンテキスト
- 33K
- 入力
- text
- 出力
- embeddings
minimaxMiniMax: MiniMax M2
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
- コンテキスト
- 205K
- 入力
- text
- 出力
- text
qwenQwen: Qwen3 VL 32B Instruct
Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text...
- コンテキスト
- 131K
- 入力
- text · image
- 出力
- text
ibm-graniteIBM: Granite 4.0 Micro
Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models released by IBM. They are fine-tuned for long...
- コンテキスト
- 131K
- 入力
- text
- 出力
- text
openaiOpenAI: GPT-5 Image Mini
GPT-5 Image Mini combines OpenAI's advanced language capabilities, powered by GPT-5 Mini, with GPT Image 1 Mini for efficient image generation. This natively multimodal model features superior instruction following, text...
- コンテキスト
- 400K
- 入力
- file · image · text
- 出力
- image · text
anthropicAnthropic: Claude Haiku 4.5
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
- コンテキスト
- 200K
- 入力
- text · image · file
- 出力
- text
anthropicAnthropic: Claude Haiku 4.5 (batch)
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
- コンテキスト
- 200K
- 入力
- text · image · file
- 出力
- text
qwenQwen: Qwen3 VL 8B Thinking
Qwen3-VL-8B-Thinking is the reasoning-optimized variant of the Qwen3-VL-8B multimodal model, designed for advanced visual and textual reasoning across complex scenes, documents, and temporal sequences. It integrates enhanced multimodal alignment and...
- コンテキスト
- 131K
- 入力
- image · text
- 出力
- text
qwenQwen: Qwen3 VL 8B Instruct
Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...
- コンテキスト
- 262K
- 入力
- image · text
- 出力
- text
openaiOpenAI: GPT-5 Image
GPT-5 Image combines OpenAI's GPT-5 model with state-of-the-art image generation capabilities. It offers major improvements in reasoning, code quality, and user experience while incorporating GPT Image 1's superior instruction following,...
- コンテキスト
- 400K
- 入力
- image · text · file
- 出力
- image · text
googleGoogle: Nano Banana (Gemini 2.5 Flash Image)
Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation,...
- コンテキスト
- 33K
- 入力
- image · text
- 出力
- image · text
qwenQwen: Qwen3 VL 30B A3B Thinking
Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Thinking variant enhances reasoning in STEM, math, and complex tasks. It excels...
- コンテキスト
- 262K
- 入力
- text · image
- 出力
- text
qwenQwen: Qwen3 VL 30B A3B Instruct
Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception...
- コンテキスト
- 262K
- 入力
- text · image
- 出力
- text
openaiOpenAI: GPT-5 Pro
GPT-5 Pro 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...
- コンテキスト
- 400K
- 入力
- image · text · file
- 出力
- text
openaiOpenAI: GPT-5 Pro (batch)
GPT-5 Pro 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...
- コンテキスト
- 400K
- 入力
- image · text · file
- 出力
- text
z-aiZ.ai: GLM 4.6
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...
- コンテキスト
- 205K
- 入力
- text
- 出力
- text
anthropicAnthropic: Claude Sonnet 4.5
Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...
- コンテキスト
- 1M
- 入力
- text · image · file
- 出力
- text
anthropicAnthropic: Claude Sonnet 4.5 (batch)
Claude Sonnet 4.5 is Anthropic’s most advanced Sonnet model to date, optimized for real-world agents and coding workflows. It delivers state-of-the-art performance on coding benchmarks such as SWE-bench Verified, with...
- コンテキスト
- 1M
- 入力
- text · image · file
- 出力
- text
deepseekDeepSeek: DeepSeek V3.2 Exp
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
- コンテキスト
- 164K
- 入力
- text
- 出力
- text