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smollm2-360m-instruct

LM-STUDIO MLX

llama · 360M · bf16

Marginal

Mar 4, 2026 · Apple M4

qwen/qwen3.8-27b

LM-STUDIO MLX

qwen3_5 · 27B · 8bit

Excellent

Aug 19, 2026 · Apple M4 Max

Global Score
52 vs 80
Hardware Fit
100 vs 52
Quality Score
32 vs 92

Hardware

smollm2-360m-instr… qwen/qwen3.8-27b
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… qwen/qwen3.8-27b
Tokens/sec121.116.1
First chunk106 ms14 ms
TTFT106 ms5.8 s
Load timeN/A8.5 s
Memory usage0.7 GB0.0 GB
Memory %2%0%

HW Fit Score Breakdown

smollm2-360m-instruct

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

qwen/qwen3.8-27b

Speed
17/50
TTFT
5/20
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

qwen/qwen3.8-27b

Reasoning
19/20
Coding
16/20
Instruction
17/20
Structured
15/15
Math
15/15
Multilingual
10/10
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong

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