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URL: https://willitrunai.com/can-run/magistral-small-2507-on-m2-max-96gb

⇱ Magistral Small 2507 on MacBook Pro M2 Max 96GB? YES

Can Magistral Small 2507 run on MacBook Pro M2 Max 96GB?

YES — Runs Great

S87Excellent
○Estimated from fit model

Magistral Small 2507 needs ~28.3 GB VRAM. MacBook Pro M2 Max 96GB has 69.1 GB. With Q4_K_M quantization, expect ~17 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: Balanced
Share:

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) — 28.3 GB, 17.0 tok/s, Runs well
28.3 GB required69.1 GB available
41% VRAM used

Fit status

Runs well

Decode

17.0 tok/s

TTFT

11364 ms

Safe context

131K

Memory

28.3 GB / 69.1 GB

Memory breakdown

Weights14.6 GB
KV Cache2.4 GB
Runtime0.9 GB
Headroom10.4 GB

See how fast it feels

See how fast it feelsMagistral Small 2507 on MacBook Pro M2 Max 96GB
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: 17.0 tok/s decode · 11.4s TTFT (warm) · 43 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

WorkloadGradeFitDecodeTTFTContext
ChatSRuns well17.0 tok/s6199 ms131K
CodingSRuns well17.0 tok/s11364 ms131K
Agentic CodingSRuns well17.0 tok/s16530 ms131K
ReasoningSRuns well17.0 tok/s13431 ms131K
RAGSRuns well17.0 tok/s20663 ms131K

Quantization options

How Magistral Small 2507 (24B params) fits at each quantization level on MacBook Pro M2 Max 96GB (69.1 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
9.4 GB
LowA82
Q3_K_S
3
11.8 GB
LowA83
NVFP4
4
13.4 GB
MediumA83
Q4_K_M
4
14.6 GB
MediumA83
Q5_K_M
5
17.3 GB
HighA84
Q6_K
6
19.7 GB
HighA84
Q8_0
8
25.7 GB
Very HighS86
F16Best for your GPU
16
49.2 GB
MaximumS89

Get started

Copy-paste commands to run Magistral Small 2507 on your machine.

Run

ollama run magistral

Your hardware

More models your MacBook Pro M2 Max 96GB can run

ModelParamsGradeDecodeCapabilities
👁 Alibaba
Qwen3-Coder 30B A3B Instruct		30.5BS35.1 tok/s
👁 Alibaba
Qwen 3.5 27B		27BS15.2 tok/s
👁 Alibaba
Qwen 3.6 27B		27BS11.6 tok/s
👁 Alibaba
Qwen 3.6 35B A3B		35BS32.4 tok/s
👁 Alibaba
Qwen3-VL 30B A3B Instruct		30BS36.3 tok/s

Frequently asked questions

See all results for MacBook Pro M2 Max 96GBSee all hardware for Magistral Small 2507