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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 RTX PRO 6000 Blackwell Server Edition 96GB

Can it run?

Can RTX PRO 6000 Blackwell Server Edition 96GB run SmolVLM 500M Instruct?

CUsable

Runs well

Using Q6_K in Ollama

Capabilities:

Fit status

Runs well

Decode

1408.6 tok/s

TTFT

350 ms

Safe context

128K

Memory

12.0 GB / 96.0 GB

Memory breakdown

Weights0.4 GB
KV Cache0.8 GB
Runtime1.2 GB
Headroom9.6 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingCRuns well1408.6 tok/s350 ms256K
ChatCRuns well1408.6 tok/s350 ms64K
CodingCRuns well1408.6 tok/s350 ms128K
RAGCRuns well1408.6 tok/s350 ms256K
ReasoningCRuns well1408.6 tok/s350 ms128K

Quantization options

How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
0.2 GB
LowD29
Q3_K_S
3
0.2 GB
LowD29
NVFP4
4
0.3 GB
MediumD30
Q4_K_M
4
0.3 GB
MediumD30
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 RTX PRO 6000 Blackwell Server Edition 96GBSee all hardware for SmolVLM 500M Instruct