text model · Mistral · macOS

Can I run Devstral Small on Apple M4 Pro (24GB)?

Compatibility verdict VRAM threshold engine

Yes, but tight GPU accelerated ~16 tok/s est.

Yes. Devstral Small runs on Apple M4 Pro (24GB) at Q4_K_M (~15.4 GB of ~16 GB usable).

Needs ~15.4 GB Device usable ~16 GB

Fits at Q4_K_M (~15.4 GB of ~16 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 (24GB) leaves ~0.6 GB of headroom.

Q4_K_M needed: ~15.4 GB
Usable on device: ~16 GB
Device memory: 24 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~16 GB usable

Q2_K

~12.1 GB

Q3_K_M

~13.7 GB

Q4_K_M

~15.4 GB

Q5_K_M

~19.1 GB

Q6_K

~21.7 GB

Q8_0

~25.3 GB

FP16

~49.2 GB

The line marks Apple M4 Pro (24GB)'s ~16 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.

Power draw: ~140 W
Electricity / 1M tokens: ~$0.36
Pays for itself after: ~14,279M tok

At ~$0.15/kWh and the estimated ~16 tok/s, a million generated tokens costs about $0.36 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,999 Apple M4 Pro (24GB) pays for itself after roughly 14,279 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands macOS

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama

$ ollama run devstral:24b

llama.cpp

$ llama-cli -hf mistralai/Devstral-Small-2507_gguf:Q4_K_M

LM Studio

$ lms get mistralai/Devstral-Small-2507_gguf

Model Mistral

Parameters: 24B
Q4_K_M size: 13.35 GB
Q8_0 size: 23.33 GB
Context: 128k
Ollama tag: devstral:24b

Full Devstral Small requirements →

Device macOS

Memory: 24 GB unified
Usable for weights: ~16 GB
Power draw: ~140 W
Best runtime: Ollama (MLX backend, preview) / MLX direct

Best models for Apple M4 Pro (24GB) →

You could also run

Run Devstral Small on other hardware

Apple M4 (24GB)Nvidia GeForce RTX 4090 (24GB)Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)32GB RAM Laptop (CPU/iGPU only)

FAQ

Can Apple M4 Pro (24GB) run Devstral Small?

Yes. Devstral Small runs on Apple M4 Pro (24GB) at Q4_K_M (~15.4 GB of ~16 GB usable).

How much memory does Devstral Small need?

It is a tight fit on Apple M4 Pro (24GB). At Q4_K_M the weights are ~13.35 GB; with KV cache and runtime overhead, budget ~15.4 GB at a 4k context.

What is the best tool to run Devstral Small 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.

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Markdown

[![Devstral Small on Apple M4 Pro (24GB)](https://localmodel.run/badge/devstral-small/apple-m4-pro-24gb.svg)](https://localmodel.run/can-i-run/devstral-small/apple-m4-pro-24gb)

Sources

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.