Is CodeLlama-7b-python-hf or Qwen3-8B smaller?

CodeLlama-7b-python-hf is smaller at Q4_K_M: 3.80 GiB against 4.68 GiB.

Which uses less memory at long context?

Qwen3-8B — its KV cache at 32K context is 3.6x smaller, because of how its attention layers cache.

Model comparison

CodeLlama-7b-python-hf vs Qwen3-8B

At Q4_K_M, CodeLlama-7b-python-hf is the smaller download — 4,081,004,288 bytes against 5,027,783,488. At long context the gap widens: Qwen3-8B's KV cache at 32K is 3.6× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	CodeLlama-7b-python-hf	Qwen3-8B
Parameters	6.7B	8.2B
Architecture	llama	qwen3
Layers	32	36
Native context	16,384	40,960
Mixture of experts	no	no
Quantizations published	12	51
Smallest quantization	2.63 GiB	2.12 GiB
Q4_K_M	3.80 GiB	4.68 GiB
Licence	llama2	apache-2.0

KV cache by context

the term that decides long-context viability

Context	CodeLlama-7b-python-hf	Qwen3-8B	Ratio
4,096	2.00 GiB	0.56 GiB	3.56×
8,192	4.00 GiB	1.13 GiB	3.56×
16,384	8.00 GiB	2.25 GiB	3.56×
32,768	16.00 GiB	4.50 GiB	3.56×
65,536	32.00 GiB	9.00 GiB	3.56×
131,072	64.00 GiB	18.00 GiB	3.56×