Model comparison
Qwen3-Coder-30B-A3B-Instruct vs Cydonia-v4.1-MS3.2-Magnum-Diamond-24B
These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Qwen3-Coder-30B-A3B-Instruct's KV cache at 32K is 1.7× smaller, which usually matters more than the difference in weights.
From the file· summed bytes, KV per layer
Side by side
| Qwen3-Coder-30B-A3B-Instruct | Cydonia-v4.1-MS3.2-Magnum-Diamond-24B | |
|---|---|---|
| Parameters | 30.5B | 23.6B |
| Architecture | qwen3moe | llama |
| Layers | 48 | 40 |
| Native context | 262,144 | 131,072 |
| Mixture of experts | yes, 128 experts | no |
| Quantizations published | 46 | 23 |
| Smallest quantization | 7.46 GiB | 4.91 GiB |
| Q4_K_M | 17.28 GiB | — |
| Licence | apache-2.0 | apache-2.0 |
KV cache by context
the term that decides long-context viability
| Context | Qwen3-Coder-30B-A3B-Instruct | Cydonia-v4.1-MS3.2-Magnum-Diamond-24B | Ratio |
|---|---|---|---|
| 4,096 | 0.38 GiB | 0.63 GiB | 1.67× |
| 8,192 | 0.75 GiB | 1.25 GiB | 1.67× |
| 16,384 | 1.50 GiB | 2.50 GiB | 1.67× |
| 32,768 | 3.00 GiB | 5.00 GiB | 1.67× |
| 65,536 | 6.00 GiB | 10.00 GiB | 1.67× |
| 131,072 | 12.00 GiB | 20.00 GiB | 1.67× |