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smollm2-360m-instruct

LM-STUDIO MLX

llama · 360M · bf16

Marginal

Mar 4, 2026 · Apple M4

qwen/qwen3-8b

LM-STUDIO MLX

qwen3 · 8B · 4bit

Excellent

Mar 5, 2026 · Apple M4 Pro

Global Score
52 vs 89
Hardware Fit
100 vs 95
Quality Score
32 vs 87

Hardware

smollm2-360m-instr… qwen/qwen3-8b
MachineMacBook AirMac mini
CPUApple M4Apple M4 Pro
Cores1014
RAM32 GB64 GB
GPUApple M4Apple M4 Pro
OSmacOS 26.3macOS 15.7.4
Archarm64arm64
Power Modebalancedbalanced

Performance

smollm2-360m-instr… qwen/qwen3-8b
Tokens/sec121.133.4
First chunk106 ms257 ms
TTFT106 ms257 ms
Load timeN/AN/A
Memory usage0.7 GB4.3 GB
Memory %2%7%

HW Fit Score Breakdown

smollm2-360m-instruct

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

qwen/qwen3-8b

Speed
45/50
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

qwen/qwen3-8b

Reasoning
19/20
Coding
14/20
Instruction
16/20
Structured
15/15
Math
13/15
Multilingual
10/10
Reasoning: Strong Coding: Adequate Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong
View smollm2-360m-instr… details | View qwen/qwen3-8b 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