How much VRAM does SmolVLM 500M Instruct need?

SmolVLM 500M Instruct (0.5B parameters) requires approximately 10.4 GB of memory with Q6_K quantization.

What is the best quantization for SmolVLM 500M Instruct?

The recommended quantization for SmolVLM 500M Instruct is Q6_K, which balances quality and memory efficiency.

Can it run?

Yes, NVIDIA H100 80GB can run SmolVLM 500M Instruct with a C grade (Runs well). Expected decode speed: 2532.6 tok/s.

CUsable

Runs well

Using Q6_K in Ollama

Capabilities:

Fit status

Runs well

Decode

2532.6 tok/s

TTFT

350 ms

Safe context

123K

Memory

10.4 GB / 80.0 GB

Weights0.4 GB

KV Cache0.8 GB

Runtime1.2 GB

Headroom8.0 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	2954.7 tok/s	350 ms	246K
Chat	C	Runs well	2954.7 tok/s	350 ms	61K
Coding	C	Runs well	2532.6 tok/s	350 ms	123K
RAG	C	Runs well	2954.7 tok/s	350 ms	246K
Reasoning	C	Runs well	2954.7 tok/s	350 ms	123K

How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	0.2 GB	Low	D29
Q3_K_S	3	0.2 GB	Low	D29
NVFP4	4

HuggingFace

huggingface-cli download hf-ggml-org--smolvlm-500m-instruct-gguf

Upgrade options

MacBook Pro M3 Max 128GBBudget pick

C252 tok/s decode

~$2,499 MSRP

Mac Studio M1 Ultra 128GBBest value

C462 tok/s decode

~$3,999 MSRP