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
kwaivgi logokwaivgi

Kling: Video O1

Kling Video O1 is a video generation model from Kuaishou. It supports text and image inputs with video output, enabling text-to-video and image-to-video workflows. It is suited for cinematic content...

上下文
暂未提供
输入
text · image
输出
video
视频输出: $0.112 每秒
查看模型详情 →
minimax logominimax

MiniMax: Hailuo 2.3

Hailuo 2.3 is a video generation model from MiniMax. It accepts text prompts and reference images as input and generates video output, supporting both text-to-video and image-to-video workflows. It is...

上下文
暂未提供
输入
text · image
输出
video
视频输出: $0.0817 每秒
查看模型详情 →
moonshotai logomoonshotai

MoonshotAI: Kimi K2.6

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and...

上下文
262K
输入
text · image
输出
text
输入: $0.65输出: $3.41每百万 Token
查看模型详情 →
mistralai logomistralai

Mistral: Voxtral Mini TTS

Voxtral Mini TTS is Mistral's text-to-speech model featuring zero-shot voice cloning and multilingual support. It converts text input into natural-sounding audio output.

上下文
4K
输入
text
输出
speech
字符: $16 每百万字符
查看模型详情 →
google logogoogle

Google: Gemini Embedding 2 Preview

Gemini Embedding 2 Preview is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It...

上下文
8K
输入
text · image · file · audio · video
输出
embeddings
输入: $0.2每百万 Token
查看模型详情 →
anthropic logoanthropic

Anthropic: Claude Opus 4.7

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

上下文
1M
输入
text · image · file
输出
text
输入: $5输出: $25每百万 Token
查看模型详情 →
anthropic logoanthropic

Anthropic: Claude Opus 4.7 (batch)

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

上下文
1M
输入
text · image · file
输出
text
输入: $2.5输出: $12.5每百万 Token
查看模型详情 →
alibaba logoalibaba

Alibaba: Wan 2.7

Wan 2.7 is a video generation model from Alibaba. It supports text-to-video, image-to-video with first and last frame control, and reference-to-video, where multiple reference images guide the style and content...

上下文
暂未提供
输入
text · image
输出
video
视频输出: $0.1 每秒
查看模型详情 →
bytedance logobytedance

ByteDance: Seedance 2.0

Seedance 2.0 is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It is particularly strong at preserving character consistency,...

上下文
暂未提供
输入
text · image · video · audio
输出
video
Video (with audio): $0.1512 每秒Video (no audio): $0.1512 每秒
查看模型详情 →
bytedance logobytedance

ByteDance: Seedance 2.0 Fast

Seedance 2.0 Fast is a video generation model from ByteDance. It supports text-to-video, image-to-video with first and last frame control, and multimodal reference-to-video. It prioritizes generation speed and lower cost...

上下文
暂未提供
输入
text · image · video · audio
输出
video
Video (with audio): $0.0907 每秒Video (no audio): $0.0907 每秒
查看模型详情 →
z-ai logoz-ai

Z.ai: GLM 5.1

GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on...

上下文
205K
输入
text
输出
text
输入: $1.4输出: $4.4每百万 Token
查看模型详情 →
cohere logocohere

Cohere: Rerank 4 Pro

Cohere's AI search foundation model for enhancing the relevance of information surfaced within search and RAG systems. Features a 32K context window, multilingual support across 100+ languages, no data pre-processing...

上下文
33K
输入
text
输出
rerank
搜索单位: $0.0025 每次搜索
查看模型详情 →
cohere logocohere

Cohere: Rerank 4 Fast

Cohere's AI search foundation model for enhancing the relevance of information surfaced within search and RAG systems. Features a 32K context window, multilingual support across 100+ languages, no data pre-processing...

上下文
33K
输入
text
输出
rerank
搜索单位: $0.002 每次搜索
查看模型详情 →
cohere logocohere

Cohere: Rerank v3.5

Rerank v3.5 is designed to reorder search results for improved relevance. It supports multi-aspect and semi-structured data reranking over 100+ languages. Ideal for refining results from semantic or keyword search...

上下文
4K
输入
text
输出
rerank
搜索单位: $0.001 每次搜索
查看模型详情 →
google logogoogle

Google: Gemma 4 26B A4B

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

上下文
262K
输入
image · text · video
输出
text
输入: $0.0765输出: $0.255每百万 Token
查看模型详情 →
google logogoogle

Google: Gemma 4 26B A4B (free)

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

上下文
262K
输入
image · text · video
输出
text
输入: 免费输出: 免费每百万 Token
查看模型详情 →
google logogoogle

Google: Gemma 4 31B

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

上下文
262K
输入
image · text · video
输出
text
输入: $0.09输出: $0.34每百万 Token
查看模型详情 →
google logogoogle

Google: Gemma 4 31B (free)

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

上下文
262K
输入
image · text · video
输出
text
输入: 免费输出: 免费每百万 Token
查看模型详情 →
qwen logoqwen

Qwen: Qwen3.6 Plus

Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...

上下文
1M
输入
text · image · video
输出
text
输入: $0.325输出: $1.95每百万 Token
查看模型详情 →
z-ai logoz-ai

Z.ai: GLM 5V Turbo

GLM-5V-Turbo is Z.ai’s first native multimodal agent foundation model, built for vision-based coding and agent-driven tasks. It natively handles image, video, and text inputs, excels at long-horizon planning, complex coding,...

上下文
203K
输入
image · text · video
输出
text
输入: $1.2输出: $4每百万 Token
查看模型详情 →
arcee-ai logoarcee-ai

Arcee AI: Trinity Large Thinking

Trinity Large Thinking is a powerful open source reasoning model from the team at Arcee AI. It shows strong performance in PinchBench, agentic workloads, and reasoning tasks. Launch video: https://youtu.be/Gc82AXLa0Rg?si=4RLn6WBz33qT--B7...

上下文
262K
输入
text
输出
text
输入: $0.25输出: $0.8每百万 Token
查看模型详情 →
x-ai logox-ai

SpaceXAI: Grok 4.20 Multi-Agent

Grok 4.20 Multi-Agent is a variant of SpaceXAI’s Grok 4.20 designed for collaborative, agent-based workflows. Multiple agents operate in parallel to conduct deep research, coordinate tool use, and synthesize information...

上下文
2M
输入
text · image · file
输出
text
输入: $1.25输出: $2.5每百万 Token
查看模型详情 →
x-ai logox-ai

SpaceXAI: Grok 4.20

Grok 4.20 is a reasoning model from SpaceXAI with industry-leading speed and agentic tool calling capabilities. It combines the lowest hallucination rate on the market with strict prompt adherance, delivering...

上下文
2M
输入
text · image · file
输出
text
输入: $1.25输出: $2.5每百万 Token
查看模型详情 →
google logogoogle

Google: Lyria 3 Pro Preview

Full-length songs are priced at $0.08 per song. Lyria 3 is Google's family of music generation models, available through the Gemini API. With Lyria 3, you can generate high-quality, 48kHz...

上下文
1.0M
输入
text · image
输出
text · audio
歌曲生成: $0.08 每首歌曲
查看模型详情 →