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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

mlx-community/gemma-3-1b-it-8bit

LM-STUDIO GGUF
Good

Mar 5, 2026 · Apple M4

Global Score
66 vs 72
Hardware Fit
100 vs 99
Quality Score
52 vs 61

Hardware

hf.co/empero-ai/Qw… mlx-community/gemm…
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… mlx-community/gemm…
Tokens/sec40.486.3
First chunk93 ms253 ms
TTFT93 ms253 ms
Load time2.7 sN/A
Memory usage4.7 GB1.1 GB
Memory %30%4%

HW Fit Score Breakdown

hf.co/empero-ai/Qwen3.8…

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

mlx-community/gemma-3-1…

Speed
50/50
TTFT
20/20
Memory
29/30

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

mlx-community/gemma-3-1…

Reasoning
7/20
Coding
14/20
Instruction
16/20
Structured
14/15
Math
2/15
Multilingual
8/10
Reasoning: Weak Coding: Adequate 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