模型 · NovaRouter

跳到主要内容

模型对话文档密钥

667 个模型获取密钥

模型对话文档密钥

NovaRouter

InfAPI 由 Inf Lab 提供，是独立的模型网关前端。介绍来自公开元数据，价格和能否调用以本网关为准。

产品

模型对话文档密钥

开发

快速开始鉴权对话补全https://infapi.cc

站点

infapi.ccInf Lab

© 2026 Inf Lab

模型

按模态、上下文、价格、参数和供应商筛选。价格是本网关标价。

输入模态

文本图像文件音频视频

上下文长度

不限32K 及以上128K 及以上200K 及以上1M 及以上

输入价格

不限免费输入低于 $0.50 / 百万输入低于 $2 / 百万输入低于 $10 / 百万

支持的参数

工具调用推理结构化输出温度

只看本网关可调用

模型作者

OpenAI127Google58Qwen51Anthropic35Mistral32智谱20DeepSeek18NVIDIA16Recraft16xAI16Microsoft13MiniMax13ByteDance Seed11ElevenLabs11Cohere9Meta9Moonshot9Perplexity9Voyage9Black Forest Labs8Meta8腾讯8Fish Audio7Aion Labs6ByteDance6OpenRouter6阿里巴巴6Amazon5Sentence Transformers5Upstage5小米5HeyGen4Inception4Liquid4Poolside4Sakana4Sourceful4Thinking Machines4Cloudflare3Deepgram3InclusionAI3Intfloat3Krea3Nous Research3Respan3Sao10K3ScaleDown3TheDrummer3TypeSafe3Unbiased3可灵3智源3阶跃星辰3IBM Granite2Inference.net2Morph2Nace2Nex AGI2Perceptron2Reka2Relace2Runway2thenlper2Anthracite1Arcee1AssemblyAI1Canopy Labs1Cognitive Computations1Dots1Fireworks1Gryphe1hexgrad1jaredpalmer1Mancer1Prism1Sesame1Together1Undi951Writer1美团1

搜索模型、供应商或能力

排序

显示 37 / 667 · 目录更新于 2026-10-14 14:24 UTC

LiquidAI: LFM2.5-Embedding-350M (free)LFM2.5-Embedding-350M is a text embedding model from Liquid AI. It produces 1,024-dimensional embeddings for retrieval and semantic search. Successful…by Liquid · 2026年8月18日512 上下文免费输入免费输出
VoyageAI by MongoDB: voyage-code-4voyage-code-4 is a code embedding model from Voyage AI, a MongoDB company. It is designed for coding agents and code retrieval, with Matryoshka embedd…by Voyage · 2026年8月13日32K 上下文$0.12 输入$0 输出
VoyageAI by MongoDB: voyage-multimodal-3.5voyage-multimodal-3.5 is a state-of-the-art multimodal embedding model capable of vectorizing not only text, images, and video individually, but also…by Voyage · 2026年7月27日32K 上下文$0.12 输入$0 输出
VoyageAI by MongoDB: voyage-4-litevoyage-4-lite is a lightweight, general-purpose embedding model optimized for low latency and cost. Enabled by Matryoshka learning and quantization-aw…by Voyage · 2026年7月27日32K 上下文$0.02 输入$0 输出
VoyageAI by MongoDB: voyage-4voyage-4 is a general-purpose (including multilingual) embedding model optimized for retrieval/search and AI applications. voyage-4 supports embedding…by Voyage · 2026年7月27日32K 上下文$0.06 输入$0 输出
VoyageAI by MongoDB: voyage-4-largevoyage-4-large is a state-of-the-art general-purpose and multilingual embedding optimized for retrieval quality. Enabled by Matryoshka learning and qu…by Voyage · 2026年7月27日32K 上下文$0.12 输入$0 输出
NVIDIA: Nemotron 3 Embed 1B (free)NVIDIA Nemotron 3 Embed 1B is an open text embedding model from NVIDIA, optimized for high-throughput, low-latency retrieval. It is suited for enterpr…by NVIDIA · 2026年7月16日33K 上下文免费输入免费输出
Google: Gemini Embedding 2Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic…by Google · 2026年5月20日8K 上下文$0.2 输入$0 输出
Google: Gemini Embedding 2 (batch)Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic…by Google · 2026年5月20日8K 上下文$0.1 输入$0 输出
Google: Gemini Embedding 2 PreviewGemini Embedding 2 Preview is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for…by Google · 2026年4月17日8K 上下文$0.2 输入$0 输出
Perplexity: Embed V1 4Bpplx-embed-v1 -4B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized…by Perplexity · 2026年3月16日32K 上下文$0.03 输入$0 输出
Perplexity: Embed V1 0.6Bpplx-embed-v1-0.6B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized…by Perplexity · 2026年3月16日32K 上下文$0.004 输入$0 输出
NVIDIA: Llama Nemotron Embed VL 1B V2 (free)The Llama Nemotron Embed VL 1B V2 embedding model is optimized for multimodal question-answering retrieval. The model can embed 'documents' in the for…by NVIDIA · 2026年2月25日131K 上下文免费输入免费输出
Thenlper: GTE-BaseThe gte-base embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, delivering efficient and effective se…by thenlper · 2025年11月18日512 上下文$0.005 输入$0 输出
Thenlper: GTE-LargeThe gte-large embedding model converts English sentences, paragraphs and moderate-length documents into a 1024-dimensional dense vector space, deliver…by thenlper · 2025年11月18日512 上下文$0.01 输入$0 输出
Intfloat: E5-Large-v2The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy…by Intfloat · 2025年11月18日512 上下文$0.01 输入$0 输出
Intfloat: E5-Base-v2The e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-qualit…by Intfloat · 2025年11月18日512 上下文$0.005 输入$0 输出
Intfloat: Multilingual-E5-LargeThe multilingual-e5-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector s…by Intfloat · 2025年11月18日512 上下文$0.01 输入$0 输出
Sentence Transformers: paraphrase-MiniLM-L6-v2The paraphrase-MiniLM-L6-v2 embedding model converts sentences and short paragraphs into a 384-dimensional dense vector space, producing high-quality…by Sentence Transformers · 2025年11月18日512 上下文$0.005 输入$0 输出
Sentence Transformers: all-MiniLM-L12-v2The all-MiniLM-L12-v2 embedding model maps sentences and short paragraphs into a 384-dimensional dense vector space, producing efficient and high-qual…by Sentence Transformers · 2025年11月18日512 上下文$0.005 输入$0 输出
BAAI: bge-base-en-v1.5The bge-base-en-v1.5 embedding model converts English sentences and paragraphs into 768-dimensional dense vectors, delivering efficient, high-quality…by 智源 · 2025年11月18日512 上下文$0.005 输入$0 输出
Sentence Transformers: multi-qa-mpnet-base-dot-v1The multi-qa-mpnet-base-dot-v1 embedding model transforms sentences and short paragraphs into a 768-dimensional dense vector space, generating high-qu…by Sentence Transformers · 2025年11月18日512 上下文$0.005 输入$0 输出
BAAI: bge-large-en-v1.5The bge-large-en-v1.5 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-fi…by 智源 · 2025年11月18日512 上下文$0.01 输入$0 输出
BAAI: bge-m3The bge-m3 embedding model encodes sentences, paragraphs, and long documents into a 1024-dimensional dense vector space, delivering high-quality seman…by 智源 · 2025年11月18日8K 上下文$0.01 输入$0 输出
Sentence Transformers: all-mpnet-base-v2The all-mpnet-base-v2 embedding model encodes sentences and short paragraphs into a 768-dimensional dense vector space, providing high-fidelity semant…by Sentence Transformers · 2025年11月17日512 上下文$0.005 输入$0 输出
Sentence Transformers: all-MiniLM-L6-v2The all-MiniLM-L6-v2 embedding model maps sentences and short paragraphs into a 384-dimensional dense vector space, enabling high-quality semantic rep…by Sentence Transformers · 2025年11月17日512 上下文$0.005 输入$0 输出
Mistral: Mistral Embed 2312Mistral Embed is a specialized embedding model for text data, optimized for semantic search and RAG applications. Developed by Mistral AI in late 2023…by Mistral · 2025年10月31日8K 上下文$0.1 输入$0 输出
Google: Gemini Embedding 001gemini-embedding-001 provides a unified cutting edge experience across domains, including science, legal, finance, and coding. This embedding model ha…by Google · 2025年10月31日20K 上下文$0.15 输入$0 输出
OpenAI: Text Embedding Ada 002text-embedding-ada-002 is OpenAI's legacy text embedding model.by OpenAI · 2025年10月30日8K 上下文$0.1 输入$0 输出
OpenAI: Text Embedding Ada 002 (batch)text-embedding-ada-002 is OpenAI's legacy text embedding model.by OpenAI · 2025年10月30日8K 上下文$0.05 输入$0 输出
Mistral: Codestral Embed 2505Mistral Codestral Embed is specially designed for code, perfect for embedding code databases, repositories, and powering coding assistants with state-…by Mistral · 2025年10月30日8K 上下文$0.15 输入$0 输出
OpenAI: Text Embedding 3 Largetext-embedding-3-large is OpenAI's most capable embedding model for both english and non-english tasks. Embeddings are a numerical representation of t…by OpenAI · 2025年10月30日8K 上下文$0.13 输入$0 输出
OpenAI: Text Embedding 3 Large (batch)text-embedding-3-large is OpenAI's most capable embedding model for both english and non-english tasks. Embeddings are a numerical representation of t…by OpenAI · 2025年10月30日8K 上下文$0.065 输入$0 输出
OpenAI: Text Embedding 3 Smalltext-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text tha…by OpenAI · 2025年10月30日8K 上下文$0.02 输入$0 输出
OpenAI: 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 tha…by OpenAI · 2025年10月30日8K 上下文$0.01 输入$0 输出
Qwen: Qwen3 Embedding 8BThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. This…by Qwen · 2025年10月28日33K 上下文$0.01 输入$0 输出
Qwen: Qwen3 Embedding 4BThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. This…by Qwen · 2025年10月28日33K 上下文$0.02 输入$0 输出