{"slug":"cohere-embed","name":"Cohere Embed","domain":"cohere.com","verdict":"As of 2026-07-13, ChatGPT, Claude, Gemini, Grok collectively rank Cohere Embed #3 of 7 for embeddings model api. Source: https://modelsagree.com/product/cohere-embed (modelsagree.com, CC BY 4.0).","best_rank":3,"categories":1,"entries":[{"slug":"best-embeddings-model-api","title":"Best embeddings model API","rank":3,"of":7,"score":11,"appearances":4,"modelRanks":{"ChatGPT":5,"Claude":3,"Gemini":1,"Grok":4},"reason":"Exceptional multilingual retrieval and search accuracy in production, featuring built-in compression (binary and int8 quantization) to drastically reduce index storage costs, and Matryoshka dimension scaling.","reasons":[{"model":"Gemini","reason":"Exceptional multilingual retrieval and search accuracy in production, featuring built-in compression (binary and int8 quantization) to drastically reduce index storage costs, and Matryoshka dimension scaling."},{"model":"Claude","reason":"The strongest enterprise package — natively multimodal (text + images/PDF pages), ~128k-token context for long documents, excellent multilingual coverage, built-in int8/binary compression, and deployable via AWS Bedrock, Azure, or private VPC where data residency matters; near-tie with Gemini Embedding on pure text quality"},{"model":"Grok","reason":"Strong multilingual support across 100+ languages, balanced enterprise performance, and competitive pricing with solid retrieval scores"},{"model":"ChatGPT","reason":"A production-friendly multilingual, multimodal model with an exceptional 128K context window, mixed text-image/PDF input, flexible dimensions, compression options, and strong enterprise deployment choices"}],"fixes":[{"model":"ChatGPT","fix":"Pure text retrieval quality and price-performance trail the leaders—not for teams optimizing solely for best text recall per dollar"},{"model":"Claude","fix":"Pricier than rivals and its raw text-retrieval edge over Voyage is unclear, so solo devs and cost-sensitive startups get less for their money than enterprises do."},{"model":"Gemini","fix":"Ranks lower in specialized code retrieval compared to technical domain-specific models, and has a complex pricing structure for multimodal queries."},{"model":"Grok","fix":"Increase max sequence length and push further on specialized domain accuracy"}],"updated":"2026-07-13","rank_history":{"days":["2026-06-29","2026-06-30","2026-07-08","2026-07-09","2026-07-10","2026-07-12","2026-07-13"],"ranks":[8,2,2,4,3,2,2]},"api":"https://modelsagree.com/api/v1/best/best-embeddings-model-api.json"}],"page":"https://modelsagree.com/product/cohere-embed","check":"https://modelsagree.com/check?q=Cohere%20Embed","updated":"2026-08-10T18:18:45.051Z","attribution":"modelsagree.com, CC BY 4.0"}