Model comparison
c4ai-command-r-v01 vs Qwen3-30B-A3B-Thinking-2507
At Q4_K_M, Qwen3-30B-A3B-Thinking-2507 is the smaller download — 18,556,685,824 bytes against 21,527,051,232.
From the file· summed bytes, KV per layer
Side by side
| c4ai-command-r-v01 | Qwen3-30B-A3B-Thinking-2507 | |
|---|---|---|
| Parameters | 35.0B | 30.5B |
| Architecture | command-r | qwen3moe |
| Layers | — | 48 |
| Native context | — | 262,144 |
| Mixture of experts | no | yes, 128 experts |
| Quantizations published | 31 | 51 |
| Smallest quantization | 7.94 GiB | 7.05 GiB |
| Q4_K_M | 20.05 GiB | 17.28 GiB |
| Licence | apache-2.0 | apache-2.0 |
KV cache by context
the term that decides long-context viability
| Context | c4ai-command-r-v01 | Qwen3-30B-A3B-Thinking-2507 | Ratio |
|---|---|---|---|
| 4,096 | — | 0.38 GiB | — |
| 8,192 | — | 0.75 GiB | — |
| 16,384 | — | 1.50 GiB | — |
| 32,768 | — | 3.00 GiB | — |
| 65,536 | — | 6.00 GiB | — |
| 131,072 | — | 12.00 GiB | — |