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hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 23, 2026 · Apple M1 Pro

lfm2.5-1.2b-instruct-mlx

LM-STUDIO MLX

lfm2 · 1.2B · 8bit

Good

Mar 4, 2026 · Apple M4

Global Score
66 vs 68
Hardware Fit
100 vs 100
Quality Score
52 vs 54

Hardware

hf.co/empero-ai/Qw… lfm2.5-1.2b-instru…
MachineMacBook ProMacBook Air
CPUApple M1 ProApple M4
Cores1010
RAM16 GB32 GB
GPUApple M1 ProApple M4
OSmacOS 26.6.2macOS 26.3
Archarm64arm64
Power Modebalancedbalanced

Performance

hf.co/empero-ai/Qw… lfm2.5-1.2b-instru…
Tokens/sec40.477.3
First chunk93 ms177 ms
TTFT93 ms177 ms
Load time2.7 sN/A
Memory usage4.7 GB1.2 GB
Memory %30%4%

HW Fit Score Breakdown

hf.co/empero-ai/Qwen3.8…

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

lfm2.5-1.2b-instruct-mlx

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

Quality

hf.co/empero-ai/Qwen3.8…

Reasoning
15/20
Coding
9/20
Instruction
8/20
Structured
1/15
Math
15/15
Multilingual
4/10
Reasoning: Adequate Coding: Weak Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Weak

lfm2.5-1.2b-instruct-mlx

Reasoning
10/20
Coding
7/20
Instruction
16/20
Structured
12/15
Math
1/15
Multilingual
8/10
Reasoning: Weak Coding: Weak Instruction Following: Strong Structured Output: Strong Math: Poor 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