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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 GTX 1060 6GB

Can it run?

Can GTX 1060 6GB run SmolVLM 500M Instruct?

CUsable

Runs well

Using Q6_K in Ollama

Capabilities:

Fit status

Runs well

Decode

118.9 tok/s

TTFT

1628 ms

Safe context

32K

Memory

3.0 GB / 6.0 GB

Memory breakdown

Weights0.4 GB
KV Cache0.8 GB
Runtime1.2 GB
Headroom0.6 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingCRuns well118.9 tok/s2368 ms64K
ChatCRuns well118.9 tok/s888 ms16K
CodingCRuns well118.9 tok/s1628 ms32K
RAGCRuns well118.9 tok/s2959 ms64K
ReasoningCRuns well118.9 tok/s1924 ms32K

Quantization options

How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on GTX 1060 6GB (6.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
0.2 GB
LowD30
Q3_K_S
3
0.2 GB
LowD30
NVFP4
4
0.3 GB
MediumD31
Q4_K_M
4
0.3 GB
MediumD31
Q5_K_M
5
0.4 GB
HighD31
Q6_K
6
0.4 GB
HighD31
Q8_0
8
0.5 GB
Very HighD31
F16Best for your GPU
16
1.0 GB
MaximumD33

Get started

HuggingFace
huggingface-cli download hf-ggml-org--smolvlm-500m-instruct-gguf
See all results for GTX 1060 6GBSee all hardware for SmolVLM 500M Instruct