mlx-community/meta-llama-3.1-8b-instruct

LM-STUDIO MLX

llama · 8B · 4bit

Good

Mar 5, 2026 · Apple M4 Pro

qwen2.5-math-1.5b-instruct

LM-STUDIO MLX

qwen2 · 1.5B · 4bit

Marginal

Mar 4, 2026 · Apple M4

Global Score

77 vs 45

Hardware Fit

100 vs 99

Quality Score

67 vs 22

Hardware

mlx-community/meta… qwen2.5-math-1.5b-…

MachineMac miniMacBook Air

CPUApple M4 ProApple M4

Cores1410

RAM64 GB32 GB

GPUApple M4 ProApple M4

OSmacOS 15.7.4macOS 26.3

Archarm64arm64

Power Modebalancedbalanced

Performance

mlx-community/meta… qwen2.5-math-1.5b-…

Tokens/sec54.391.7

First chunk277 ms205 ms

TTFT277 ms205 ms

Load timeN/AN/A

Memory usage4.2 GB0.8 GB

Memory %7%3%

HW Fit Score Breakdown

mlx-community/meta-llam…

Speed

50/50

TTFT

20/20

Memory

30/30

qwen2.5-math-1.5b-instr…

Speed

50/50

TTFT

20/20

Memory

29/30

Quality

mlx-community/meta-llam…

Reasoning

11/20

Coding

14/20

Instruction

14/20

Structured

15/15

Math

4/15

Multilingual

9/10

Reasoning: Adequate Coding: Adequate Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Strong

qwen2.5-math-1.5b-instr…

Reasoning

2/20

Coding

0/20

Instruction

3/20

Structured

1/15

Math

14/15

Multilingual

2/10

Reasoning: Poor Coding: Poor Instruction Following: Poor Structured Output: Poor Math: Strong Multilingual: Poor

View mlx-community/meta… details | View qwen2.5-math-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