Qwen3.5-27B
2recorded runs
286.6best tok/s
1verified
What the Qwen3.5-27B numbers mean
The fastest verified result on our board is 286.6 output tok/s on an Radeon AI Pro R9700 at MQ4-AWQ with a 4096-token context. That is about 3.5 ms per generated token — 500 tokens takes roughly 1.7 seconds. Prompt processing on the same record runs at 435.7 tok/s, so a 2,000-token prompt is read in about 4.6 seconds. Peak VRAM was measured at 17.5 GB.
How much VRAM does Qwen3.5-27B need?
Qwen3.5-27B has 28.0B 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) | 18.9 GB | 24 GB |
| Q8_0 (8-bit) | 35.0 GB | 48 GB |
| FP16 (16-bit) | 65.2 GB | 80 GB |
Fastest GPUs for this model (best tok/s)
- Radeon AI Pro R9700286.6
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| Bonsai-27B | 28B | 15.8 GB |
| Godoter-27B | 28B | 15.8 GB |
| Huihui-Qwen3.8-27B-abliterated | 28B | 15.8 GB |
| Qwen3.6-27B | 28B | 15.8 GB |
| Qwen3.6-27B-i1 | 28B | 15.8 GB |
| Qwen3.6-27B-MTP | 28B | 15.8 GB |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| Radeon AI Pro R9700 · 32 GB | Qwen3.5-27B | MQ4-AWQ | hipfire 0.2.0+3730b58 | 4096 | 286.6 ✓ | 435.7 | 17.5 | src |
| Radeon AI Pro R9700 · 32 GB | Qwen3.5-27B | Q4_K_XL | llama.cpp — | 2048 | 26.7 … | 1099.5 | — | src |