EmbeddingsAvailable now

mxbai-embed-large v1

Make your knowledge instantly discoverable.

Tiny but mighty English embeddings that led their MTEB class at release, matching models 20x larger. Matryoshka dimensions, binary quantization.

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Good for

01Build semantic search and RAG over organizational knowledge.
02Detect similarities, classify content and eliminate duplicates.
03Optimize vector storage and retrieval costs.

Information systems & search
Helpdesk & support

Key facts

Model origin: Mixedbread AI
Context window: 512 tokens
Size: 335M
Modalities: text → vector
Languages: EN
Dimensions: 1024
API model id: Model id published at launch
Availability: Available now. Regional rollout is shown in your Console. Ask us about your region.

Your data boundary

Prompts and outputs are not stored by default. Knowledge or Memory data that your organization intentionally persists is encrypted, pinned to the selected region, isolated to authorized organizational scopes, and never used to train shared or third-party models.

Works well with

ChatAvailable nowQwen 3.8Enterprise chat, coding & 1M context ChatAvailable nowGemma 4Efficient AI for everyday workflows DecisionsAvailable nowClefIntelligent, confidence-scored decisions

More models

Qwen 3.8 Gemma 4 Clef FLUX.2 [klein]Whisper large v3 Qwen3 Embedding 0.6B Kokoro DeepSeek 4.1 Flash GLM 5.3

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