{"schema":"postcutoff/model@1","as_of":"2026-11-13T13:49:00+01:00","url":"https://postcutoff.com/m/cohere-embed-v4/","md":"https://postcutoff.com/m/cohere-embed-v4/index.md","disclosure":{"written_by":"AI agents (Claude Opus 5.5 in Claude Code)","editor":"human editor","policy":"https://postcutoff.com/about/"},"license":null,"id":"cohere-embed-v4","name":"Cohere Embed v4","org":"Cohere","family":"Embed","released":"2025-04","status":"current","type":"embedding","modality_in":["text","image","pdf"],"modality_out":["text"],"open_weights":false,"model_license":"proprietary","context_window":128000,"max_output":null,"knowledge_cutoff":null,"pricing":null,"price_line":"Price not published","access":[{"provider":"Cohere API","model_id":"embed-v4.0","endpoint":"https://api.cohere.com/v2/embed","docs":"https://docs.cohere.com/docs/cohere-embed"},{"provider":"AWS Bedrock","model_id":"cohere.embed-v4:0","docs":"https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-cohere-embed-v4.html"}],"capabilities":[{"name":"Interleaved text+image (PDF) embeddings","detail":"Embeds text, images and mixed text/image documents such as PDFs into one vector space.","first":false,"discovered":"launch","source":"https://docs.cohere.com/docs/cohere-embed"},{"name":"128K-token input with Matryoshka dims","detail":"Up to 128K tokens per input; output dimension selectable 256/512/1024/1536.","first":false,"discovered":"launch","source":"https://docs.cohere.com/docs/models"}],"entry":null,"notes":"Output is vectors (modality_out text used as placeholder). Release month (Apr 2025) from memory, not re-verified. Pricing not verified (Cohere pricing page shows only Model Vault hourly rates).","verified":"2026-09-29","body_md":"Multimodal embeddings for search/RAG over long docs and scanned PDFs.\n\n```bash\ncurl https://api.cohere.com/v2/embed -H \"Authorization: Bearer $CO_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"embed-v4.0\",\"input_type\":\"search_document\",\"embedding_types\":[\"float\"],\"texts\":[\"hello world\"]}'\n```\n\nSources: https://docs.cohere.com/docs/models , https://docs.cohere.com/docs/cohere-embed","page_url":"https://postcutoff.com/m/cohere-embed-v4/","standing":{"kind":"embedding","newer_count":5,"newer":[{"id":"embeddinggemma-2","name":"EmbeddingGemma 2","org":"Google DeepMind","released":"2026-10-06","page_url":"https://postcutoff.com/m/embeddinggemma-2/"},{"id":"cohere-embed-v5-fast","name":"Cohere Embed 5 Fast","org":"Cohere","released":"2026-09-30","page_url":"https://postcutoff.com/m/cohere-embed-v5-fast/"},{"id":"cohere-embed-v5-pro","name":"Cohere Embed 5 Pro","org":"Cohere","released":"2026-09-30","page_url":"https://postcutoff.com/m/cohere-embed-v5-pro/"},{"id":"gemini-embedding-2","name":"Gemini Embedding 2","org":"Google DeepMind","released":"2026-04-22","page_url":"https://postcutoff.com/m/gemini-embedding-2/"},{"id":"cohere-rerank-4","name":"Cohere Rerank 4 (Pro / Fast)","org":"Cohere","released":"2025-12-11","page_url":"https://postcutoff.com/m/cohere-rerank-4/"}],"before":null,"after":{"id":"cohere-rerank-4","name":"Cohere Rerank 4 (Pro / Fast)","org":"Cohere","released":"2025-12-11","page_url":"https://postcutoff.com/m/cohere-rerank-4/"},"weights":"closed","licence":"proprietary","licence_permissive":false,"summary":"Closed weights; access is hosted only."}}