Back to leaderboard

smollm2-360m-instruct

LM-STUDIO MLX

llama · 360M · bf16

Marginal

Mar 4, 2026 · Apple M4

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

LM-STUDIO MLX

qwen2 · 1.5B · 8bit

Good

Mar 4, 2026 · Apple M4

Global Score
52 vs 70
Hardware Fit
100 vs 100
Quality Score
32 vs 57

Hardware

smollm2-360m-instr… qwen2.5-coder-1.5b…
MachineMacBook AirMacBook Air
CPUApple M4Apple M4
Cores1010
RAM32 GB32 GB
GPUApple M4Apple M4
OSmacOS 26.3macOS 26.3
Archarm64arm64
Power Modebalancedbalanced

Performance

smollm2-360m-instr… qwen2.5-coder-1.5b…
Tokens/sec121.158.4
First chunk106 ms234 ms
TTFT106 ms234 ms
Load timeN/AN/A
Memory usage0.7 GB1.5 GB
Memory %2%5%

HW Fit Score Breakdown

smollm2-360m-instruct

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

qwen2.5-coder-1.5b-inst…

Speed
50/50
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

qwen2.5-coder-1.5b-inst…

Reasoning
9/20
Coding
12/20
Instruction
13/20
Structured
12/15
Math
4/15
Multilingual
7/10
Reasoning: Weak Coding: Adequate Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Adequate
View smollm2-360m-instr… details | View qwen2.5-coder-1.5b… 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