Jina AI
Jina Embeddings v3
Aktuell
4.0MDownloads1.1KLikesSep 2024Veröffentlicht8K TokenKontextCC-BY-NC-4.0Lizenz86 StarkQualität
Jina Embeddings v3 (0.5720000267028809B parameters) requires approximately 4.9 GB of VRAM with F16 quantization. For the best balance of quality and speed, we recommend hardware with at least 6 GB of VRAM.
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ollama run jina/jina-embeddings-v3Quick specs
Parameters0.57B
Architecturedense
Context8K tokens
Modalityembedding
Min RAM0.2 GB
Rec. RAM1.2 GB (F16)
LicenseCC-BY-NC-4.0
FamilyJina Embeddings
✓ RAG
About this model
- •Extended Sequence Length:: Supports up to 8192 tokens with RoPE
- •Task-Specific Embedding:: Customize embeddings through the task argument with the following options:
- •retrieval.query: Used for query embeddings in asymmetric retrieval tasks
- •retrieval.passage: Used for passage embeddings in asymmetric retrieval tasks
- •separation: Used for embeddings in clustering and re-ranking applications
Schnellauswahl
Beste Hardware
Top-Empfehlungen für Jina Embeddings v3
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 | 0.2 GB | Low | — |
Q3_K_S | 3 | 0.3 GB | Low | — |
NVFP4 | 4 | 0.3 GB | Medium | — |
Q4_K_M | 4 | 0.3 GB | Medium | — |
Q5_K_M | 5 | 0.4 GB | High | — |
Q6_K | 6 | 0.5 GB | High | — |
Q8_0 | 8 | 0.6 GB | Very High | — |
F16 | 16 | 1.2 GB | Maximum | — |
Hardware-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights1.2 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — Jina Embeddings v3
Siehe auch