How much VRAM does SmolVLM 500M Instruct need?

SmolVLM 500M Instruct (0.5B parameters) requires approximately 3.4 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, RTX 3080 10GB can run SmolVLM 500M Instruct with a C grade (Runs well). Expected decode speed: 574.6 tok/s.

CUsable

Runs well

Using Q6_K in Ollama

Capabilities:

Fit status

Runs well

Decode

574.6 tok/s

TTFT

350 ms

Safe context

47K

Memory

3.4 GB / 10.0 GB

Weights0.4 GB

KV Cache0.8 GB

Runtime1.2 GB

Headroom1.0 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	606.5 tok/s	464 ms	94K
Chat	C	Runs well	606.5 tok/s	350 ms	23K
Coding	C	Runs well	574.6 tok/s	350 ms	47K
RAG	C	Runs well	606.5 tok/s	580 ms	94K
Reasoning	C	Runs well	606.5 tok/s	377 ms	47K

How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on RTX 3080 10GB (10.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	0.2 GB	Low	D30
Q3_K_S	3	0.2 GB	Low	D30
NVFP4	4

HuggingFace

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

Upgrade options

MacBook Pro M4 16GBBudget pick

C90.7 tok/s decode

~$599 MSRP

MacBook Pro M1 Pro 16GBBest value

C136.5 tok/s decode

~$1,999 MSRP