hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16
OLLAMA GGUFqwen35 · 1.94B · BF16
Aug 22, 2026 · Apple M1 Pro
qwen2.5-1.5b-instruct
LM-STUDIO MLXqwen2 · 1.5B · 8bit
Mar 4, 2026 · Apple M4
Global Score
66 vs 69
Hardware Fit
100 vs 100
Quality Score
52 vs 56
Hardware
hf.co/empero-ai/Qw… qwen2.5-1.5b-instr…
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… qwen2.5-1.5b-instr…
Tokens/sec40.258.1
First chunk325 ms211 ms
TTFT325 ms211 ms
Load time3.1 sN/A
Memory usage4.7 GB1.5 GB
Memory %30%5%
HW Fit Score Breakdown
hf.co/empero-ai/Qwen3.8…
Speed
50/50
TTFT
20/20
Memory
30/30
qwen2.5-1.5b-instruct
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
qwen2.5-1.5b-instruct
Reasoning
9/20
Coding
10/20
Instruction
10/20
Structured
14/15
Math
5/15
Multilingual
8/10
Reasoning: Weak Coding: Adequate Instruction Following: Adequate Structured Output: Strong Math: Weak Multilingual: Strong
Run yours and compare
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest