Can I Run SmolLM2 on 16 GB system RAM?

Written by Jakub Rusinowski · Last updated November 20, 2024

Yes — comfortably

Yes, comfortably — SmolLM2 1.7B Instruct at Q8_0 needs about 4.2 GB of the 12.8 GB usable on 16 GB system RAM, leaving ~8.6 GB spare and running at ~24.2 tok/s (estimated), with room for about 8,192 tokens of context.

Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~24.2 tok/s

16 GB system RAM — what it gives a model

Usable memory for models12.8 GB
Memory bandwidth90 GB/s

SmolLM2 on 16 GB system RAM: memory by quantization

QuantMemory neededFits 12.8 GB?Max contextEst. speedDownload
F165.8 GB✓ Yes8K~15.4 tok/s3.4 GB
Q8_04.2 GB✓ Yes8K~24.2 tok/s1.8 GB
Q6_K3.8 GB✓ Yes8K~28.5 tok/s1.4 GB
Q5_K_M3.6 GB✓ Yes8K~31 tok/s1.2 GB
Q4_K_M3.4 GB✓ Yes8K~33.8 tok/s1 GB
Q3_K_M3.1 GB✓ Yes8K~39.9 tok/s0.7 GB
Q2_K3 GB✓ Yes8K~44.3 tok/s0.6 GB

Which SmolLM2 sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
SmolLM2 1.7B Instruct3.4 GB✓ Fits~33.8 tok/s
SmolLM2 360M Instruct1.4 GB✓ Fits~125.1 tok/s

What to watch out for

Recommended setup

llama.cpp (CPU build) or Ollama — both run without a GPU

How these numbers are calculated

FAQ

Can I run SmolLM2 on 16 GB system RAM?

Yes, comfortably — SmolLM2 1.7B Instruct at Q8_0 needs about 4.2 GB of the 12.8 GB usable on 16 GB system RAM, leaving ~8.6 GB spare and running at ~24.2 tok/s (estimated), with room for about 8,192 tokens of context.

Which quantization of SmolLM2 should I use on 16 GB system RAM?

Q8_0 — it needs about 4.2 GB of the 12.8 GB available, downloads as roughly 1.8 GB, and runs at an estimated 24.2 tokens/sec with up to 8K of context.

What limits SmolLM2 on 16 GB system RAM?

Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.

Which runtime should I use?

llama.cpp (CPU build) or Ollama — both run without a GPU

Other RAM Capacities

Other Models on 16 GB system RAM

SmolLM2 on GPUs

What This Model Is Good At

Model & Tools

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