lfm2.5-1.2b-instruct-mlx

lfm2 · 1.2B · 8bit

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 4, 2026
Top 49% Compare
Global Score
68 /100
Good
Hardware Fit
100/100
Quality
54/100

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Hardware

Machine
MacBook Air
CPU
Apple M4
Cores
10 total (4 perf + 6 eff)
Frequency
2.4 GHz
RAM
32 GB LPDDR5
GPU
Apple M4
OS
macOS 26.3
Arch
arm64
Power Mode
balanced

Performance

Tokens/sec
77.3
Standard deviation
±4.4
First chunk latency
177 ms
Time to first token
177 ms
Load time
N/A
Memory usage
1.2 GB (4%)
Total tokens
1001

Score breakdown

Speed
50/50
Time to first token
20/20
Memory
30/30

Quality

Reasoning
10/20
Coding
7/20
Instruction following
16/20
Structured output
12/15
Math
1/15
Multilingual
8/10

Category levels

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

Metadata

Spec version
0.2.1
Runtime
LM Studio 0.4.6+1
Model format
MLX
Hardware profile
BALANCED
Result hash
1bde63920d8b07ea9584b15a4e7bbe67332d1d744ea1d075ab0a9c48cb22763b

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 68/100). Category profile: Reasoning: Weak, Coding: Weak, Instruction Following: Strong, Structured Output: Strong, Math: Poor, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 14% (peak 16%)

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