Back to leaderboard

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

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 22, 2026 · Apple M1 Pro

qwen3.5-0.8b-mlx

LM-STUDIO MLX

qwen3_5 · 0.8B · 8bit

Good

Mar 3, 2026 · Apple M4

Global Score
66 vs 60
Hardware Fit
100 vs 96
Quality Score
52 vs 44

Hardware

hf.co/empero-ai/Qw… qwen3.5-0.8b-mlx
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… qwen3.5-0.8b-mlx
Tokens/sec40.2108.0
First chunk325 ms2568 ms
TTFT325 ms2.6 s
Load time3.1 sN/A
Memory usage4.7 GB1.0 GB
Memory %30%3%

HW Fit Score Breakdown

hf.co/empero-ai/Qwen3.8…

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

qwen3.5-0.8b-mlx

Speed
50/50
TTFT
16/20
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

qwen3.5-0.8b-mlx

Reasoning
10/20
Coding
3/20
Instruction
11/20
Structured
12/15
Math
3/15
Multilingual
5/10
Reasoning: Weak Coding: Poor Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Adequate
View hf.co/empero-ai/Qw… details | View qwen3.5-0.8b-mlx 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