text model · Mistral · macOS
Can I run Mixtral 8x7B on Apple M4 Pro (48GB)?
Yes. Mixtral 8x7B runs on Apple M4 Pro (48GB) at Q4_K_M (~28.9 GB of ~32 GB usable).
Fits at Q4_K_M (~28.9 GB of ~32 GB usable) but with little headroom. Close other apps, or drop to a 2k context to free about a gigabyte.
That figure is at a 4k context and moves about ±15% as context length changes. Apple M4 Pro (48GB) leaves ~3.1 GB of headroom.
- Q4_K_M needed
- ~28.9 GB
- Usable on device
- ~32 GB
- Device memory
- 48 GB
- Best quant
- Q4_K_M
Which quant fits
Run it
Pick your tool. All 3 load the same Q4_K_M weights.
ollama run mixtral:8x7b llama-cli -hf MaziyarPanahi/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_M lms get MaziyarPanahi/Mixtral-8x7B-Instruct-v0.1-GGUF - Parameters
- 46.7B (MoE, 12.9B active)
- Q4_K_M size
- 26.49 GB
- Q8_0 size
- 46.22 GB
- Context
- 32k
- Ollama tag
- mixtral:8x7b
- Memory
- 48 GB unified
- Usable for weights
- ~32 GB
- Power draw
- ~140 W
- Best runtime
- Ollama (MLX backend) / MLX direct
You could also run
Run Mixtral 8x7B on other hardware
FAQ
Can Apple M4 Pro (48GB) run Mixtral 8x7B?
Yes. Mixtral 8x7B runs on Apple M4 Pro (48GB) at Q4_K_M (~28.9 GB of ~32 GB usable).
How much memory does Mixtral 8x7B need?
It is a tight fit on Apple M4 Pro (48GB). At Q4_K_M the weights are ~26.49 GB; with KV cache and runtime overhead, budget ~28.9 GB at a 4k context. It is a Mixture-of-Experts model (46.7B total / 12.9B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Mixtral 8x7B 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.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/mixtral-8x7b/apple-m4-pro-48gb) Sources
- apple.com/newsroom/2024/10/apple-introduces-m4-pro-and-m4-max
- apple.com/newsroom/2024/10/new-macbook-pro-features-m4-family-of-chips-and-apple-intelligence
- blog.peddals.com
- github.com/ml-explore
- github.com/raullenchai
- huggingface.co/MaziyarPanahi
- huggingface.co/mistralai
- lmstudio.ai
- ollama.com/library/mixtral
- ollama.com/library/mixtral/tags
- support.apple.com/en-us/103253
- support.apple.com/en-us/121553
- support.apple.com/en-us/121555
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.