qwen2.5-coder-1.5b-instruct-mlx

qwen2 · 1.5B · 8bit

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 4, 2026
Top 45% Compare
Global Score
70 /100
Good
Hardware Fit
100/100
Quality
57/100

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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
58.4
Standard deviation
±2.6
First chunk latency
234 ms
Time to first token
234 ms
Load time
N/A
Memory usage
1.5 GB (5%)
Total tokens
1090

Score breakdown

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

Quality

Reasoning
9/20
Coding
12/20
Instruction following
13/20
Structured output
12/15
Math
4/15
Multilingual
7/10

Category levels

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

Metadata

Spec version
0.2.1
Runtime
LM Studio 0.4.6+1
Model format
MLX
Hardware profile
BALANCED
Result hash
03e0683b7ccf990c5b200d551d17ae719f3b8b2d86a6dc9f0a14d0aeda67744b

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 70/100). Category profile: Reasoning: Weak, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Poor, Multilingual: Adequate.

Bench Environment

Power: AC CPU load: avg 12% (peak 14%)

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