Text model · SmolLM2
SmolLM2 135M requirements
SmolLM2 family · 0.135B params · released 2024-11-02 · 2.6M Ollama pulls. Minimum to run at Q4_K_M: Apple M1 (8GB).
Quantization sizes
| Quantization | Size on disk |
|---|---|
| Q2_K | 0.1 GB est |
| Q3_K_M | 0.1 GB est |
| Q4_K_M (default) | 0.105 GB |
| Q5_K_M | 0.1 GB est |
| Q6_K | 0.1 GB est |
| Q8_0 | 0.145 GB |
| FP16 | 0.3 GB est |
Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.
Run it
ollama run smollm2:135m llama-cli -hf bartowski/SmolLM2-135M-Instruct-GGUF:Q4_K_M lms get bartowski/SmolLM2-135M-Instruct-GGUF Which devices can run SmolLM2 135M?
Apple Silicon Macs
RAM-only laptops
iPhone & iPad
Android
NVIDIA GPUs
AMD GPUs
FAQ
How much VRAM or RAM does SmolLM2 135M need?
At Q4_K_M, SmolLM2 135M needs about 1 GB (weights ~0.105 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~1 GB.
Can SmolLM2 135M run on a laptop?
Yes, SmolLM2 135M fits on a 16 GB machine at Q4_K_M and runs on Apple Silicon or a 12 GB+ GPU comfortably.
Can I use SmolLM2 135M commercially?
Yes. SmolLM2 135M is licensed Apache-2.0, which permits commercial use.
Hugging Face's smallest SLM. 135M params, fits in ~105MB at Q4_K_M. Designed for microcontrollers and on-device inference. Trained on 2T tokens (FineWeb-Edu, DCLM, The Stack).
Sources
Memory figures are estimates. See methodology.