Qwen3.8-9B-Distill
3recorded runs
76.4best tok/s
1verified
What the Qwen3.8-9B-Distill numbers mean
The fastest verified result on our board is 46.4 output tok/s on an RTX 2060 Super at Q6_K with a 8192-token context. That is about 21.5 ms per generated token — 500 tokens takes roughly 10.8 seconds. Prompt processing on the same record runs at 1295.0 tok/s, so a 2,000-token prompt is read in about 1.5 seconds. Peak VRAM was measured at 6.7 GB. Across the 3 records we hold for this model the range is 22.9–76.4 tok/s on 3 GPUs, because quantisation, context length and the engine build all move the number.
How much VRAM does Qwen3.8-9B-Distill need?
Qwen3.8-9B-Distill has 9.0B parameters. These estimates use the same formula as the VRAM calculator: weights, plus about 15% for a moderate-context KV cache and runtime overhead, plus a small engine floor.
| Quantisation | Estimated VRAM | Smallest card that fits |
|---|---|---|
| Q4_K_M (4-bit) | 6.6 GB | 8 GB |
| Q8_0 (8-bit) | 11.8 GB | 16 GB |
| FP16 (16-bit) | 21.5 GB | 32 GB |
Fastest GPUs for this model (best tok/s)
- RTX 306076.4
- RTX 2060 Super46.4
- RTX 208022.9
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| Carnice-9b | 9B | 5.1 GB |
| DeepSeek-V4-Pro-Qwen3.5-9B-MTP | 9B | 5.1 GB |
| Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-i1 | 9B | 5.1 GB |
| NVIDIA-Nemotron-Nano-9B-v2 | 9B | 5.1 GB |
| Ornith-1.0-9B | 9B | 5.1 GB |
| Qwen3-VL-8B-Instruct | 9B | 5.1 GB |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| RTX 2060 Super · 8 GB | Qwen3.8-9B-Distill | Q6_K | llama.cpp b10449 (0d9ceae1e38291035605613ab41a… | 8192 | 46.4 ✓ | 1295.0 | 6.7 | src |
| RTX 3060 · 12 GB | Qwen3.8-9B-Distill | Q4_K_M | llama.cpp — | 131072 | 76.4 … | 560.7 | — | src |
| RTX 2080 · 8 GB | Qwen3.8-9B-Distill | Q4_K_M | llama.cpp — | 131072 | 22.9 … | 292.4 | 6.8 | src |