DeepSeek-R1-Distill-Qwen-14B
1recorded run
35.1best tok/s
1verified
What the DeepSeek-R1-Distill-Qwen-14B numbers mean
The fastest verified result on our board is 35.1 output tok/s on an RTX 3060 x2 at Q4_K_M with a 512-token context. That is about 28.5 ms per generated token — 500 tokens takes roughly 14.3 seconds. Prompt processing on the same record runs at 1123.3 tok/s, so a 2,000-token prompt is read in about 1.8 seconds. Peak VRAM was measured at 16.5 GB.
How much VRAM does DeepSeek-R1-Distill-Qwen-14B need?
DeepSeek-R1-Distill-Qwen-14B has 15.0B 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) | 10.5 GB | 16 GB |
| Q8_0 (8-bit) | 19.1 GB | 24 GB |
| FP16 (16-bit) | 35.3 GB | 48 GB |
Fastest GPUs for this model (best tok/s)
- RTX 3060 x235.1
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| Nemotron-Cascade-14B-Thinking | 15B | 8.4 GB |
| phi-4 | 15B | 8.4 GB |
| Phi-4-reasoning | 15B | 8.4 GB |
| Phi-4-reasoning-plus | 15B | 8.4 GB |
| Qwen2.5-Coder-14B-Instruct | 15B | 8.4 GB |
| DeepSeek-Coder-V2-Lite-Instruct | 16B | 9.0 GB |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| RTX 3060 x2 · 12 GB | DeepSeek-R1-Distill-Qwen-14B | Q4_K_M | llama.cpp 13f2b28 | 512 | 35.1 ✓ | 1123.3 | 16.5 | src |