Is SmolVLM-500M-Instruct or Qwen3-4B smaller?

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

Which uses less memory at long context?

SmolVLM-500M-Instruct — its KV cache at 32K context is 3.6x smaller, because of how its attention layers cache.

Model comparison

SmolVLM-500M-Instruct vs Qwen3-4B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: SmolVLM-500M-Instruct'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

	SmolVLM-500M-Instruct	Qwen3-4B
Parameters	507M	4.0B
Architecture	llama	qwen3
Layers	32	36
Native context	8,192	40,960
Mixture of experts	no	no
Quantizations published	2	29
Smallest quantization	0.41 GiB	1.01 GiB
Q4_K_M	—	2.33 GiB
Licence	apache-2.0	—

KV cache by context

the term that decides long-context viability

Context	SmolVLM-500M-Instruct	Qwen3-4B	Ratio
4,096	0.16 GiB	0.56 GiB	3.60×
8,192	0.31 GiB	1.13 GiB	3.60×
16,384	0.63 GiB	2.25 GiB	3.60×
32,768	1.25 GiB	4.50 GiB	3.60×
65,536	2.50 GiB	9.00 GiB	3.60×
131,072	5.00 GiB	18.00 GiB	3.60×