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smollm2-360m-instruct

LM-STUDIO MLX

llama · 360M · bf16

Marginal

Mar 4, 2026 · Apple M4

qwen3.8-27b-mlx

LM-STUDIO UNKNOWN

27B

Good

Aug 17, 2026 · Apple M5 Max

Global Score
52 vs 66
Hardware Fit
100 vs 91
Quality Score
32 vs 55

Hardware

smollm2-360m-instr… qwen3.8-27b-mlx
MachineMacBook AirMacBook Pro
CPUApple M4Apple M5 Max
Cores1018
RAM32 GB64 GB
GPUApple M4Apple M5 Max
OSmacOS 26.3macOS 27.0
Archarm64arm64
Power Modebalancedbalanced

Performance

smollm2-360m-instr… qwen3.8-27b-mlx
Tokens/sec121.133.2
First chunk106 ms7 ms
TTFT106 ms311 ms
Load timeN/AN/A
Memory usage0.7 GB0.5 GB
Memory %2%1%

HW Fit Score Breakdown

smollm2-360m-instruct

Speed
50/50
TTFT
20/20
Memory
30/30

qwen3.8-27b-mlx

Speed
41/50
TTFT
20/20
Memory
30/30

Quality

smollm2-360m-instruct

Reasoning
4/20
Coding
3/20
Instruction
12/20
Structured
7/15
Math
2/15
Multilingual
4/10
Reasoning: Poor Coding: Poor Instruction Following: Adequate Structured Output: Weak Math: Poor Multilingual: Weak

qwen3.8-27b-mlx

Reasoning
19/20
Coding
13/20
Instruction
6/20
Structured
0/15
Math
14/15
Multilingual
3/10
Reasoning: Strong Coding: Adequate Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Weak

Run yours and compare

$ npm install -g metrillm@latest
$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest