text model · SmolLM3 · macOS
Can I run SmolLM3 3B on Apple M2 (16GB)?
Yes. SmolLM3 3B runs on Apple M2 (16GB) at Q4_K_M (~3 GB of ~10.5 GB usable).
Runs at Q4_K_M using ~3 GB of ~10.5 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~3 GB
- Usable on device
- ~10.5 GB
- Device memory
- 16 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
llama-cli -hf unsloth/SmolLM3-3B-GGUF:Q4_K_M lms get unsloth/SmolLM3-3B-GGUF vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
How to run it
On macOS use LM Studio (Polished GUI, ships MLX on Apple Silicon, one-click model downloads.). vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
- Parameters
- 3B
- Q4_K_M size
- 1.78 GB
- Q8_0 size
- 3.05 GB
- Context
- 128k
- Memory
- 16 GB unified
- Usable for weights
- ~10.5 GB
- Best runtime
- Ollama (llama.cpp Metal backend) / MLX
You could also run
Run SmolLM3 3B on other hardware
FAQ
Can Apple M2 (16GB) run SmolLM3 3B?
Yes. SmolLM3 3B runs on Apple M2 (16GB) at Q4_K_M (~3 GB of ~10.5 GB usable).
How much memory does SmolLM3 3B need?
Apple M2 (16GB) has room to spare. At Q4_K_M the weights are ~1.78 GB; with KV cache and runtime overhead, budget ~3 GB at a 4k context.
What is the best tool to run SmolLM3 3B on macOS?
LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.
Sources
Memory figures are estimates. See methodology.