How much VRAM does SmolVLM 500M Instruct need?

SmolVLM 500M Instruct (0.5B parameters) requires approximately 3.5 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 2080 Ti 11GB can run SmolVLM 500M Instruct with a C grade (Runs well). Expected decode speed: 465.7 tok/s.

CUsable

Runs well

Using Q6_K in Ollama

Capabilities:

Fit status

Runs well

Decode

465.7 tok/s

TTFT

416 ms

Safe context

50K

Memory

3.5 GB / 11.0 GB

Weights0.4 GB

KV Cache0.8 GB

Runtime1.2 GB

Headroom1.1 GB

Workload	Grade	Fit	Decode	TTFT	Context
Agentic Coding	C	Runs well	420.4 tok/s	670 ms	100K
Chat	C	Runs well	420.4 tok/s	350 ms	25K
Coding	C	Runs well	465.7 tok/s	416 ms	50K
RAG	C	Runs well	420.4 tok/s	837 ms	100K
Reasoning	C	Runs well	420.4 tok/s	544 ms	50K

How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on RTX 2080 Ti 11GB (11.0 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