Model comparison
Qwen2.5-Coder-1.5B-Unsensored-DPO vs Llama-3.2-1B-Instruct
These two publish different quantization sets; the table below has the exact sizes.
From the file· summed bytes, KV per layer
Side by side
| Qwen2.5-Coder-1.5B-Unsensored-DPO | Llama-3.2-1B-Instruct | |
|---|---|---|
| Parameters | 1.5B | 1.2B |
| Architecture | qwen2 | llama |
| Layers | 28 | 16 |
| Native context | 32,768 | 131,072 |
| Mixture of experts | no | no |
| Quantizations published | 48 | 39 |
| Smallest quantization | 0.41 GiB | 0.39 GiB |
| Q4_K_M | — | 0.75 GiB |
| Licence | — | — |
KV cache by context
the term that decides long-context viability
| Context | Qwen2.5-Coder-1.5B-Unsensored-DPO | Llama-3.2-1B-Instruct | Ratio |
|---|---|---|---|
| 4,096 | 0.11 GiB | 0.13 GiB | 1.14× |
| 8,192 | 0.22 GiB | 0.25 GiB | 1.14× |
| 16,384 | 0.44 GiB | 0.50 GiB | 1.14× |
| 32,768 | 0.88 GiB | 1.00 GiB | 1.14× |
| 65,536 | 1.75 GiB | 2.00 GiB | 1.14× |
| 131,072 | 3.50 GiB | 4.00 GiB | 1.14× |