text model · Qwen2.5-VL · macOS
Can I run Qwen2.5-VL 3B on Apple M4 Pro (48GB)?
Yes. Qwen2.5-VL 3B runs on Apple M4 Pro (48GB) at Q4_K_M (~4.4 GB of ~32 GB usable).
Runs at Q4_K_M using ~4.4 GB of ~32 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~4.4 GB
- Usable on device
- ~32 GB
- Device memory
- 48 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
llama-cli -hf ggml-org/Qwen2.5-VL-3B-Instruct-GGUF:Q4_K_M lms get ggml-org/Qwen2.5-VL-3B-Instruct-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
- 3.75B
- Q4_K_M size
- 3.05 GB
- Q8_0 size
- 5.1 GB
- Context
- 32k
- Memory
- 48 GB unified
- Usable for weights
- ~32 GB
- Best runtime
- Ollama (MLX backend) / MLX direct
You could also run
Run Qwen2.5-VL 3B on other hardware
FAQ
Can Apple M4 Pro (48GB) run Qwen2.5-VL 3B?
Yes. Qwen2.5-VL 3B runs on Apple M4 Pro (48GB) at Q4_K_M (~4.4 GB of ~32 GB usable).
How much memory does Qwen2.5-VL 3B need?
Apple M4 Pro (48GB) has room to spare. At Q4_K_M the weights are ~3.05 GB; with KV cache and runtime overhead, budget ~4.4 GB at a 4k context.
What is the best tool to run Qwen2.5-VL 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.