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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/SmolVLM 500M Instruct/on NVIDIA H200 141GB

Can it run?

Can NVIDIA H200 141GB run SmolVLM 500M Instruct?

CUsable

Runs well

Using Q6_K in Ollama

Capabilities:

Fit status

Runs well

Decode

4233.6 tok/s

TTFT

350 ms

Safe context

137K

Memory

16.5 GB / 141.0 GB

Memory breakdown

Weights0.4 GB
KV Cache0.8 GB
Runtime1.2 GB
Headroom14.1 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingCRuns well4233.6 tok/s350 ms273K
ChatCRuns well4233.6 tok/s350 ms68K
CodingCRuns well4233.6 tok/s350 ms137K
RAGCRuns well4233.6 tok/s350 ms273K
ReasoningCRuns well4233.6 tok/s350 ms137K

Quantization options

How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on NVIDIA H200 141GB (141.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
0.2 GB
LowD29
Q3_K_S
3
0.2 GB
LowD29
NVFP4
4
0.3 GB
MediumD29
Q4_K_M
4
0.3 GB
MediumD29
Q5_K_M
5
0.4 GB
HighD30
Q6_K
6
0.4 GB
HighD30
Q8_0
8
0.5 GB
Very HighD30
F16Best for your GPU
16
1.0 GB
MaximumD30

Get started

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

Upgrade options

Hardware that runs SmolVLM 500M Instruct well

AppleMac Studio M3 Ultra 256GBBudget pick
C584.8 tok/s decode

 

See all results for NVIDIA H200 141GBSee all hardware for SmolVLM 500M Instruct