OpenRouter publishes 2026 embedding model guide covering 37 catalog entries

OpenRouter 发布 2026 年最佳嵌入模型选型指南，覆盖 37 个目录条目

OpenRouter shortlisted embedding models from its 37-entry catalog for English RAG, multilingual, code, and text-image retrieval. The default pick is OpenAI text-embedding-3-small for its low price and 8,192-token context. For longer inputs, Voyage 4 large offers a 32,000-token window and index compatibility across Voyage 4 tiers. Qwen3-Embedding-8B is recommended for multilingual retrieval with public weights and 100+ language support. Code search goes to Voyage Code 4, while Gemini Embedding 2 and Voyage Multimodal 3.5 handle text-and-image. The free route is Nvidia Nemotron-3-Embed-1B; the cheapest paid option is Perplexity pplx-embed-v1-0.6b at $0.004 per million tokens. OpenRouter notes these checks confirm API behavior, not retrieval quality, and advises testing on your own data before building an index.