# Can I run SmolLM2 135M on Apple M1 (8GB)?

> **Yes, it runs.** Runs at Q4_K_M using ~1 GB of ~5.5 GB usable. You have room for FP16 for higher quality.

Last validated: 2026-06-15.

## Memory math
- SmolLM2 135M: 0.135B; Q4_K_M weighs 0.105 GB on disk.
- At Q4_K_M with a 4k context it needs ~1 GB (weights + KV cache + ~0.8 GB runtime overhead, ±15% with context length).
- Apple M1 (8GB): 8 GB unified, ~5.5 GB usable for model weights.
- Headroom: ~4.5 GB; it also fits FP16 for higher quality.

## How to run
Recommended quant: Q4_K_M. Best tool on macOS: LM Studio.

```sh
ollama run smollm2:135m
```

## Run SmolLM2 135M on other devices
- [8GB RAM Laptop (CPU/iGPU only)](https://localmodel.run/can-i-run/smollm2-135m/laptop-8gb)
- [iPhone 15 Pro](https://localmodel.run/can-i-run/smollm2-135m/iphone-15-pro)
- [iPhone 16](https://localmodel.run/can-i-run/smollm2-135m/iphone-16)
- [iPhone 16 Pro](https://localmodel.run/can-i-run/smollm2-135m/iphone-16-pro)
- [Generic Android Phone (8GB RAM)](https://localmodel.run/can-i-run/smollm2-135m/android-generic-8gb)
- [iPhone 17](https://localmodel.run/can-i-run/smollm2-135m/iphone-17)

## Other models that run on Apple M1 (8GB)
- [Gemma 3 4B (4B)](https://localmodel.run/can-i-run/gemma-3-4b/apple-m1-8gb)
- [Qwen3 4B (4B)](https://localmodel.run/can-i-run/qwen3-4b/apple-m1-8gb)
- [Phi-3.5-mini 3.8B (3.82B)](https://localmodel.run/can-i-run/phi-3.5-mini/apple-m1-8gb)
- [Phi-4-mini 3.8B (3.8B)](https://localmodel.run/can-i-run/phi-4-mini-3.8b/apple-m1-8gb)
- [Qwen2.5-VL 3B (3.75B)](https://localmodel.run/can-i-run/qwen2.5-vl-3b/apple-m1-8gb)
- [Qwen2.5 3B (3.09B)](https://localmodel.run/can-i-run/qwen2.5-3b/apple-m1-8gb)

Estimate, not a guarantee. Sources: https://ollama.com/library/smollm2:135m, https://huggingface.co/bartowski/SmolLM2-135M-Instruct-GGUF, https://venturebeat.com/ai/ai-on-your-smartphone-hugging-faces-smollm2-brings-powerful-models-to-the-palm-of-your-hand.
More: https://localmodel.run/can-i-run/smollm2-135m/apple-m1-8gb