text model · SmolLM3 · macOS
Can I run SmolLM3 3B on Apple M5 (32GB)?
Yes. SmolLM3 3B runs on Apple M5 (32GB) at Q4_K_M (~3 GB of ~21 GB usable).
Runs at Q4_K_M using ~3 GB of ~21 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~3 GB
- Usable on device
- ~21 GB
- Device memory
- 32 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
- 32 GB unified
- Usable for weights
- ~21 GB
- Best runtime
- MLX direct / Ollama (MLX backend)
You could also run
Run SmolLM3 3B on other hardware
FAQ
Can Apple M5 (32GB) run SmolLM3 3B?
Yes. SmolLM3 3B runs on Apple M5 (32GB) at Q4_K_M (~3 GB of ~21 GB usable).
How much memory does SmolLM3 3B need?
Apple M5 (32GB) 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.