Can Mistral Small 3.2 24B run on MacBook Pro M1 Max 64GB?

YES — Runs Great

A82Great

Estimated from fit model

Mistral Small 3.2 24B needs ~25.2 GB VRAM. MacBook Pro M1 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~15 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: Balanced

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 25.2 GB, 16.2 tok/s, Runs well

25.2 GB required46.1 GB available

55% VRAM used

Fit status

Runs well

Decode

16.2 tok/s

TTFT

11984 ms

Safe context

131K

Memory

25.2 GB / 46.1 GB

Memory breakdown

Weights14.6 GB

KV Cache2.4 GB

Runtime1.2 GB

Headroom6.9 GB

See how fast it feels

See how fast it feelsMistral Small 3.2 24B on MacBook Pro M1 Max 64GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.

Given information:
  - Speed = 60 mph (miles per hour)
  - Time  = 2.5 hours

Formula: Distance = Speed x Time

Calculation:
  Distance = 60 mph x 2.5 h
           = 150 miles

The train travels 150 miles.

Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.

Breakdown:
  - First half: 1.25 hours at 60 mph = 75 miles
  - Stop: 20 minutes (no distance)
  - Second half: 1.25 hours at 60 mph = 75 miles

Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph

The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 16.2 tok/s decode · 12.0s TTFT (warm) · 40 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Shared-memory contention still exists

The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	15.0 tok/s	7027 ms	131K
Coding	A	Runs well	15.0 tok/s	12883 ms	131K
Agentic Coding	A	Runs well	15.0 tok/s	18739 ms	131K
Reasoning	A	Runs well	15.0 tok/s	15226 ms	131K
RAG	A	Runs well	15.0 tok/s	23424 ms	131K

Quantization options

How Mistral Small 3.2 24B (24B params) fits at each quantization level on MacBook Pro M1 Max 64GB (46.1 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	9.4 GB	Low	A77
Q3_K_S	3	11.8 GB	Low	A78
NVFP4	4	13.4 GB	Medium	A78
Q4_K_M	4	14.6 GB	Medium	A79
Q5_K_M	5	17.3 GB	High	A80
Q6_K	6	19.7 GB	High	A80
Q8_0Best for your GPU	8	25.7 GB	Very High	A82
F16	16	49.2 GB	Maximum	F0

Get started

Copy-paste commands to run Mistral Small 3.2 24B on your machine.

Run

ollama run mistral-small3.2

Your hardware

More models your MacBook Pro M1 Max 64GB can run

Model	Params	Grade	Decode
Qwen3-Coder 30B A3B Instruct	30.5B	S	33.3 tok/s
Qwen 3.5 27B	27B	S	14.4 tok/s
Qwen 3.6 27B	27B	S	14.5 tok/s
Qwen 3.6 35B A3B	35B	S	30.8 tok/s
Qwen3-VL 30B A3B Instruct	30B	S	34.4 tok/s

Frequently asked questions

Can MacBook Pro M1 Max 64GB run Mistral Small 3.2 24B?

Yes, MacBook Pro M1 Max 64GB can run Mistral Small 3.2 24B with a A grade (Runs well). Expected decode speed: 15.0 tok/s.

How much VRAM does Mistral Small 3.2 24B need?

Mistral Small 3.2 24B (24B parameters) requires approximately 25.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Mistral Small 3.2 24B?

The recommended quantization for Mistral Small 3.2 24B is Q4_K_M, which balances quality and memory efficiency.

What speed will Mistral Small 3.2 24B run at on MacBook Pro M1 Max 64GB?

On MacBook Pro M1 Max 64GB, Mistral Small 3.2 24B achieves approximately 15.0 tokens per second decode speed with a time-to-first-token of 12883ms using Q4_K_M quantization.

Can MacBook Pro M1 Max 64GB run Mistral Small 3.2 24B for coding?

For coding workloads, Mistral Small 3.2 24B on MacBook Pro M1 Max 64GB receives a A grade with 15.0 tok/s and 131K context.

What context window can Mistral Small 3.2 24B use on MacBook Pro M1 Max 64GB?

On MacBook Pro M1 Max 64GB, Mistral Small 3.2 24B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

Is unified memory on MacBook Pro M1 Max 64GB as fast as VRAM for Mistral Small 3.2 24B?

Not always. MacBook Pro M1 Max 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.

See all results for MacBook Pro M1 Max 64GB See all hardware for Mistral Small 3.2 24B

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