Alibaba/Qwen · open-weights model
Qwen2.5-1.5B-Instruct
Qwen2.5-1.5B-Instruct is a 1.5B-parameter model by Alibaba/Qwen. Its smallest quant (Q4_K_M) needs at least 1.6GB of GPU-addressable memory at 8K context; it loads cleanly at a quality quant on 50 of the 50 machines we track.
- Parameters
- 1.5B
- Layers
- 28
- Max context
- 32K
- Attention
- GQA
- License
- apache-2.0
Config from Qwen/Qwen2.5-1.5B-Instruct
Quants and what they need
Measured file sizes; “needs” = weights + KV cache at 8K context + overhead.
| Quant | File size | Needs ≥ |
|---|---|---|
| Q8_0 | 1.6 GB | 2.3 GB |
| Q6_K | 1.3 GB | 1.9 GB |
| Q5_K_M | 1.1 GB | 1.8 GB |
| Q4_K_M | 1.0 GB | 1.6 GB |
What runs Qwen2.5-1.5B-Instruct
Every machine we track, graded at its best clean-fit quant.
Verdicts computed from published specs and measured GGUF sizes — how the math works.