mxbai-embed-large-v1
Free.ai (self-hosted)
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embeddings
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~100 Koffice FilterName call
mxbai-embed-large-v1 is an embeming model gebou deur mixedbread.ai. Sterkste by Semantic search, clustering, similarity.. Self-hosted on Free.ai GPUs — runs free against your daily token pool (100 tokens per roep). Released under Apache 2.0 — commercial use permitted on Free.ai.
Gebruik via API
OpenAI- versoenbaar met REST API. Genereer 'n sleutel en noem hierdie model in sekondes.
curl -X POST https://api.free.ai/v1/image/generate/ \
-H "Authorization: Bearer sk-free-..." \
-H "Content-Type: application/json" \
-d '{"model":"mxbai-embed-large-v1","prompt":"your prompt here"}'Vrae wat dikwels gevra word
mxbai-embed-large-v1 converts text into a dense vector (a list of floats) that captures meaning. Use it for semantic search, clustering, recommendation, retrieval-augmented generation (RAG), and any task where "is this text similar to that text" matters.
Tipiese dimensies is 384, 768, 1024 of 1536 afhangende van die model. BGE-M3 uitstuur 1024-dim; OpenAI Ada stel 1536 vry. Die API-reaksie sluit die dimensie in sodat jou vektor DB die regte indeks kies.
Modern embedding models (including most options on Free.ai) are trained on 100+ languages. Cross-language retrieval works — search in English, match documents in Spanish.
512 tot 8 192 inligting na gelang van die model. Lang dokumente word langer afgeknot in paragrawe voor opvou.
mxbai-embed-large-v1 loop op ons eie GPU's en is een van die goedkoopste gereedskap wat omstreeks ~100 seine per oproep van jou daaglikse vry poel getrek is. $5 = 200K ides.
Ja 98 POTT 'n lys stringe na /v1/embedings/ en mxbai-embed-large-v1 gee terug' n lys van vektore in dieselfde volgorde. Bochtch grootte na 2 048 per versoek.
L2-ormaaliseer deur verstek takiesl cos-ooreenkoms = punt produk. Pass takiesialise=SvalsName
Enige ą Pinecone, Weiviate, Qdrant, Chroma, pgvector, FAISS, LanceDB. mxbai-embed-large-v1 keer terug gewone JSON dryf; die DB sien nooit die model nie.
Ja 98 POST na /v1/embedings/ met model="mxbai-embed-large-v1". OpenAI- versoenbaarte reaksie, so bestaande kliënt biblioteke werk onveranderd. /api/ het die volledige verwysing.
Self-gehostde modelle hou jou teks op ons GPUs en gooi dit weg na die oproep terug. Premium gaan deur met 'n DPA. Ons oefen nie op jou invoere nie.
Sub-100ms for short text on self-hosted, 100–500ms on premium. Batch calls scale roughly linearly — 1,000 chunks complete in 2–10 seconds.
Yes — Free.ai grants commercial use of embeddings. Build production search, RAG pipelines, recommendation systems with no per-vector royalty.