{"slug":"gemini-embedding-2","name":"Gemini Embedding 2","domain":"google.com","verdict":"As of 2026-07-17, ChatGPT, Claude, Gemini, Grok collectively rank Gemini Embedding 2 #2 of 13 for multilingual embedding api for semantic search (one of 3 leaderboards it appears on). Source: https://modelsagree.com/product/gemini-embedding-2 (modelsagree.com, CC BY 4.0).","best_rank":2,"categories":3,"entries":[{"slug":"best-multilingual-embedding-api-for-semantic-search","title":"Best multilingual embedding API for semantic search","rank":2,"of":13,"score":11,"appearances":3,"modelRanks":{"ChatGPT":1,"Gemini":4,"Grok":2},"reason":"Best overall multilingual retrieval quality, supporting 100+ languages and cross-language search, with flexible 128–3072 dimensions and native text, image, audio, video, and PDF embeddings; strongest default when quality and multimodal headroom matter.","reasons":[{"model":"ChatGPT","reason":"Best overall multilingual retrieval quality, supporting 100+ languages and cross-language search, with flexible 128–3072 dimensions and native text, image, audio, video, and PDF embeddings; strongest default when quality and multimodal headroom matter."},{"model":"Grok","reason":"Strong multilingual MTEB performance (top ranks reported ~69.9), native multimodal (text+images/video/audio) in unified space for advanced semantic search, low latency/cost via Gemini API/Vertex AI, excellent for practitioners needing cross-modal or enterprise-grade reliability."},{"model":"Gemini","reason":"Native multimodal support (text, image, audio, video) in a single model, strong multilingual retrieval, and deep integration with the Google Cloud / Vertex AI enterprise ecosystem."}],"fixes":[{"model":"ChatGPT","fix":"Its 8,192-token limit is restrictive for long documents compared with 32K-context rivals."},{"model":"Gemini","fix":"Tied closely to the Google Cloud/Vertex AI infrastructure, where API setup, procurement, and management are more complex than developer-oriented standalone APIs."},{"model":"Grok","fix":"Not purely text-focused; multimodal limits (e.g. PDF page caps, audio/video duration) and API dependency may not suit pure text or self-hosted needs."}],"updated":"2026-07-17","api":"https://modelsagree.com/api/v1/best/best-multilingual-embedding-api-for-semantic-search.json"},{"slug":"best-multimodal-embedding-api-for-image-search","title":"Best multimodal embedding API for image search","rank":2,"of":9,"score":10,"appearances":3,"modelRanks":{"ChatGPT":4,"Gemini":3,"Grok":1},"reason":"First native unified multimodal embedding across text, images, video, audio, and documents in one vector space; top cross-modal retrieval (out","reasons":[{"model":"Grok","reason":"First native unified multimodal embedding across text, images, video, audio, and documents in one vector space; top cross-modal retrieval (out"},{"model":"Gemini","reason":"Highly scalable, cost-efficient general-purpose API featuring a large 8k token limit, native video and audio embedding capabilities, and turnkey GCP vector search integration."},{"model":"ChatGPT","reason":"Very inexpensive image embeddings, flexible 128–3072 dimensions, more than 100 languages, and one unified space spanning text, images, PDFs, audio, and video; a near-tie with Cohere when broad modality coverage matters"}],"fixes":[{"model":"ChatGPT","fix":"Newer and less independently proven on real image-retrieval workloads, with only six images per request and an 8K-token ceiling"},{"model":"Gemini","fix":"Shows poor accuracy on highly specialized domain visual layouts and is deeply dependent on the Google Cloud platform ecosystem."}],"updated":"2026-07-17","api":"https://modelsagree.com/api/v1/best/best-multimodal-embedding-api-for-image-search.json"},{"slug":"best-ai-video-understanding-api","title":"Best AI video understanding API","rank":3,"of":10,"score":6,"appearances":2,"modelRanks":{"ChatGPT":4,"Claude":2},"reason":"The strongest raw video understanding available — hours of footage in a single long-context prompt, timestamped answers, direct YouTube URL ingestion, and Gemini Flash pricing makes per-video analysis extremely cheap; Vertex's multimodal embeddings cover the vector-search side. Wins the near-tie with Twelve Labs if you'd rather assemble your own pipeline and pocket the cost savings.","reasons":[{"model":"Claude","reason":"The strongest raw video understanding available — hours of footage in a single long-context prompt, timestamped answers, direct YouTube URL ingestion, and Gemini Flash pricing makes per-video analysis extremely cheap; Vertex's multimodal embeddings cover the vector-search side. Wins the near-tie with Twelve Labs if you'd rather assemble your own pipeline and pocket the cost savings."},{"model":"ChatGPT","reason":"Near-tied with Nova on retrieval merit, with native video/audio embeddings, a shared cross-modal space, strong multilingual coverage, and convenient Gemini API or Vertex AI access."}],"fixes":[{"model":"ChatGPT","fix":"Its 120-second video-input limit and preview maturity make production-scale long-video indexing substantially more DIY."},{"model":"Claude","fix":"There is no managed video search index — you build ingestion, chunking, embedding storage, and retrieval yourself, and re-querying the same footage burns tokens unless you engineer context caching carefully."}],"updated":"2026-07-15","rank_history":{"days":["2026-07-13","2026-07-15"],"ranks":[3,null]},"api":"https://modelsagree.com/api/v1/best/best-ai-video-understanding-api.json"}],"page":"https://modelsagree.com/product/gemini-embedding-2","check":"https://modelsagree.com/check?q=Gemini%20Embedding%202","updated":"2026-08-10T18:18:45.051Z","attribution":"modelsagree.com, CC BY 4.0"}