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smollm2-360m-instruct

LM-STUDIO MLX

llama · 360M · bf16

Marginal

Mar 4, 2026 · Apple M4

qwen3.8-27b-fable-fusion-f711-gain-mlx

LM-STUDIO MLX

qwen3_5 · 27B · MXFP4

Excellent

Aug 20, 2026 · Apple M4 Max

Global Score
52 vs 88
Hardware Fit
100 vs 70
Quality Score
32 vs 96

Hardware

smollm2-360m-instr… qwen3.8-27b-fable-…
MachineMacBook AirMacBook Pro
CPUApple M4Apple M4 Max
Cores1016
RAM32 GB128 GB
GPUApple M4Apple M4 Max
OSmacOS 26.3macOS 26.5.2
Archarm64arm64
Power Modebalancedbalanced

Performance

smollm2-360m-instr… qwen3.8-27b-fable-…
Tokens/sec121.130.4
First chunk106 ms27 ms
TTFT106 ms4.4 s
Load timeN/AN/A
Memory usage0.7 GB19.9 GB
Memory %2%16%

HW Fit Score Breakdown

smollm2-360m-instruct

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

qwen3.8-27b-fable-fusio…

Speed
34/50
TTFT
6/20
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-fable-fusio…

Reasoning
19/20
Coding
19/20
Instruction
18/20
Structured
15/15
Math
15/15
Multilingual
10/10
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong
View smollm2-360m-instr… details | View qwen3.8-27b-fable-… details

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