Mixedbread AI
mxbai Embed Large
Aktuell
4.8MDownloads805LikesMar 2024Veröffentlicht1K TokenKontextApache 2.0Lizenz80 StarkQualität
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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— kopieren & einfügen, um lokal auszuführenCopy-paste commands to run mxbai Embed Large on your machine.
Run
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
Schnellauswahl
Beste Hardware
Top-Empfehlungen für mxbai Embed Large
Dieses Modell ausführen
Quantisierungsoptionen
VRAM-Schätzungen nach Quantisierungsstufe
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-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights0.7 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — mxbai Embed Large
Siehe auch