Model comparison

Qwen3-53B-A3B-2507-THINKING-TOTAL-RECALL-v2-MASTER-CODER vs Qwen3-Coder-30B-A3B-Instruct

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 1.8× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

Qwen3-53B-A3B-2507-THINKING-TOTAL-RECALL-v2-MASTER-CODERQwen3-Coder-30B-A3B-Instruct
Parameters53.0B30.5B
Architectureqwen3moeqwen3moe
Layers8448
Native context262,144262,144
Mixture of expertsyes, 128 expertsyes, 128 experts
Quantizations published2346
Smallest quantization10.22 GiB7.46 GiB
Q4_K_M—17.28 GiB
Licenceapache-2.0apache-2.0

KV cache by context

the term that decides long-context viability
ContextQwen3-53B-A3B-2507-THINKING-TOTAL-RECALL-v2-MASTER-CODERQwen3-Coder-30B-A3B-InstructRatio
4,0960.66 GiB0.38 GiB1.75×
8,1921.31 GiB0.75 GiB1.75×
16,3842.63 GiB1.50 GiB1.75×
32,7685.25 GiB3.00 GiB1.75×
65,53610.50 GiB6.00 GiB1.75×
131,07221.00 GiB12.00 GiB1.75×
Qwen3-53B-A3B-2507-THINKING-TOTAL-RECALL-v2-MASTER-CODER vs Qwen3-Coder-30B-A3B-Instruct — size, memory and hardware fit — ossmodeldb