Qwen/Qwen3-Embedding-0.6B
Qwen/Qwen3-Embedding-0.6B
Parameters
507.6M
Context
32K
Downloads
8.1M
Likes
1.2K
Architecture
qwen3
28 layers · 8 KV heads · head 128 · hidden 1024
GPU Requirements
VRAM / RAM / disk estimates by quantization and usage scenario
| Quantization | Minimum | Recommended | Production |
|---|---|---|---|
| FP1616bit | 2.6 GB RAM 32.0 · Disk 40.5 | 2.8 GB RAM 32.0 · Disk 66.5 | 3.2 GB RAM 32.0 · Disk 105.5 |
| FP88bit | 1.9 GB RAM 32.0 · Disk 39.7 | 2.1 GB RAM 32.0 · Disk 65.7 | 2.4 GB RAM 32.0 · Disk 104.7 |
| INT88bit | 1.9 GB RAM 32.0 · Disk 39.7 | 2.1 GB RAM 32.0 · Disk 65.7 | 2.4 GB RAM 32.0 · Disk 104.7 |
| AWQ4bit | 1.6 GB RAM 32.0 · Disk 39.4 | 1.8 GB RAM 32.0 · Disk 65.4 | 2.1 GB RAM 32.0 · Disk 104.4 |
| GPTQ4bit | 1.6 GB RAM 32.0 · Disk 39.4 | 1.8 GB RAM 32.0 · Disk 65.4 | 2.1 GB RAM 32.0 · Disk 104.4 |
| GGUF4bit | 1.6 GB RAM 32.0 · Disk 39.4 | 1.8 GB RAM 32.0 · Disk 65.4 | 2.1 GB RAM 32.0 · Disk 104.4 |
GPU Recommendations
1× RTX 5060 Ti
8 GB VRAM
≈ 3584 vec/s
Effective production throughput ≈ 2867.2 vectors/s
score 0.5507
1× RTX 5060 Ti
8 GB VRAM
≈ 3584 vec/s
Effective production throughput ≈ 2867.2 vectors/s
score 0.5507
8× RTX 5060 Ti
64 GB VRAM
≈ 28672 vec/s
Effective production throughput ≈ 22937.6 vectors/s
score 0.3636
2× RTX 5060 Ti
16 GB VRAM
≈ 7168 vec/s
Effective production throughput ≈ 5734.4 vectors/s
score 0.451
💬 Community — real deployment experience
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GPUs that fit (single card)
Tesla V100
16 GB VRAM
$20.3
/mo · vast
RTX 5060 Ti
8 GB VRAM
$39.7
/mo · vast
RTX 4070S Ti
16 GB VRAM
$49.5
/mo · vast
RTX 4080S
16 GB VRAM
$50.0
/mo · vast
RTX 5070
12 GB VRAM
$58.7
/mo · vast