mistralai/devstral-small-2-2512

mistral3 · 24B · 4bit

MacBook Pro (Apple M1 Pro)

32 GB · macOS 15.6.1

Tested on October 20, 2026

Top 59% Compare

Global Score

73 /100

Good

Hardware Fit

64/100

Quality

77/100

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MLX versions & conversions

Hardware

Machine: MacBook Pro
CPU: Apple M1 Pro
Cores: 10 total (8 perf + 2 eff)
Frequency: 2.4 GHz
RAM: 32 GB LPDDR5
GPU: Apple M1 Pro
OS: macOS 15.6.1
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 11.9
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 7 ms
Time to first token How fast the model starts responding — lower is better: 1.1 s
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 19.7 GB (62%)
Total tokens Total number of tokens generated across all benchmark prompts: 1026

Score breakdown

Speed

25/50

Time to first token

20/20

Memory

19/30

Quality

Reasoning

17/20

Coding

16/20

Instruction following

13/20

Structured output

14/15

Math

7/15

Multilingual

10/10

Category levels

Reasoning: Strong Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Weak Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: LM Studio
Model format: MLX
Hardware profile: BALANCED
Result hash: a11bec0e53a92b6b82b831da46fa48f21c1c290e16bf92d11516d5665547846a

Interpretation

Hardware fit: 64/100. Overall suitability: GOOD (Global 73/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Warnings

Model memory footprint is estimated via LM Studio CLI rather than measured from a fresh load.

Bench Environment

Power: AC CPU load: avg 19% (peak 20%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest