Is Qwen3-Coder-REAP-363B-A35B or DeepSeek-V4-Flash smaller?

Both publish quantizations; compare the table for the exact sizes.

Which uses less memory at long context?

DeepSeek-V4-Flash — its KV cache at 32K context is 123.0x smaller, because of how its attention layers cache.

Model comparison

Qwen3-Coder-REAP-363B-A35B vs DeepSeek-V4-Flash

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: DeepSeek-V4-Flash's KV cache at 32K is 123.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3-Coder-REAP-363B-A35B	DeepSeek-V4-Flash
Parameters	363B	291B
Architecture	qwen3moe	deepseek4
Layers	62	43
Native context	262,144	1,048,576
Mixture of experts	yes, 120 experts	yes, 256 experts
Quantizations published	19	12
Smallest quantization	94.37 GiB	76.87 GiB
Q4_K_M	204.25 GiB	—
Licence	apache-2.0	mit

KV cache by context

the term that decides long-context viability

Context	Qwen3-Coder-REAP-363B-A35B	DeepSeek-V4-Flash	Ratio
4,096	0.97 GiB	0.06 GiB	15.38×
8,192	1.94 GiB	0.06 GiB	30.76×
16,384	3.88 GiB	0.06 GiB	61.52×
32,768	7.75 GiB	0.06 GiB	123.04×
65,536	15.50 GiB	0.06 GiB	246.08×
131,072	31.00 GiB	0.06 GiB	492.16×