text model · Mistral · macOS

Can I run Devstral Small on Apple M3 Pro (18GB)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Devstral Small needs ~15.4 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.

Needs ~15.4 GB Device usable ~12 GB

Needs ~15.4 GB even at Q4_K_M, but only ~12 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 3.4 GB: Devstral Small needs roughly 15.4 GB at Q4_K_M and Apple M3 Pro (18GB) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Devstral Small is the Apple M4 (24GB) at 24 GB. See Devstral Small on Apple M4 (24GB).

Q4_K_M needed: ~15.4 GB
Usable on device: ~12 GB
Device memory: 18 GB

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Which quant fits

Quant ladder vs ~12 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 M3 Pro (18GB)'s ~12 GB budget; rungs past it are too large.

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: 18 GB unified
Usable for weights: ~12 GB
Power draw: ~70 W
Best runtime: Ollama (llama.cpp Metal backend) / MLX

Best models for Apple M3 Pro (18GB) →

What you can run instead

Run Devstral Small on other hardware

Apple M4 (24GB)Apple M4 Pro (24GB)Nvidia GeForce RTX 4090 (24GB)Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)

FAQ

Can Apple M3 Pro (18GB) run Devstral Small?

No. Devstral Small needs ~15.4 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.

How much memory does Devstral Small need?

Apple M3 Pro (18GB) does not have enough memory. 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 M3 Pro (18GB)](https://localmodel.run/badge/devstral-small/apple-m3-18gb.svg)](https://localmodel.run/can-i-run/devstral-small/apple-m3-18gb)

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.