Model comparison

gpt-oss-20b-BF16 vs Qwen3-Coder-30B-A3B-Instruct

At Q4_K_M, gpt-oss-20b-BF16 is the smaller download — 15,805,134,880 bytes against 18,556,689,568. At long context the gap widens: gpt-oss-20b-BF16's KV cache at 32K is 3.9× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

gpt-oss-20b-BF16Qwen3-Coder-30B-A3B-Instruct
Parameters20.9B30.5B
Architecturegpt-ossqwen3moe
Layers2448
Native context131,072262,144
Mixture of expertsyes, 32 expertsyes, 128 experts
Quantizations published846
Smallest quantization12.03 GiB7.46 GiB
Q4_K_M14.72 GiB17.28 GiB
Licenceapache-2.0apache-2.0

KV cache by context

the term that decides long-context viability
Contextgpt-oss-20b-BF16Qwen3-Coder-30B-A3B-InstructRatio
4,0960.11 GiB0.38 GiB3.37×
8,1920.21 GiB0.75 GiB3.66×
16,3840.39 GiB1.50 GiB3.82×
32,7680.77 GiB3.00 GiB3.91×
65,5361.52 GiB6.00 GiB3.95×
131,0723.02 GiB12.00 GiB3.98×