👁 Mixedbread AI
Mixedbread AI
mxbai Embed Large
Current
5.9MDownloads811LikesMar 2024Released1K tokensContextApache 2.0License80 StrongQuality
mxbai Embed Large (0.33500000834465027B parameters) requires approximately 4.0 GB of VRAM with F16 quantization. For the best balance of quality and speed, we recommend hardware with at least 5 GB of VRAM.
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— copy & paste to run locallyCopy-paste commands to run mxbai Embed Large on your machine.
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ollama run mxbai-embed-largeQuick specs
Parameters0.34B
Architecturedense
Context1K tokens
Modalityembedding
Min RAM0.1 GB
Rec. RAM0.7 GB (F16)
LicenseApache 2.0
Familymxbai
✓ RAG
About this model
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Quantization options
VRAM estimates by quant level
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.1 GB | Low | — |
Q3_K_S | 3 | 0.2 GB | Low | — |
NVFP4 | 4 | 0.2 GB | Medium | — |
Q4_K_M | 4 | 0.2 GB | Medium | — |
Q5_K_M | 5 | 0.2 GB | High | — |
Q6_K | 6 | 0.3 GB | High | — |
Q8_0 | 8 | 0.4 GB | Very High | — |
F16 | 16 | 0.7 GB | Maximum | — |
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights0.7 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
Frequently asked questions
FAQ — mxbai Embed Large
See also