hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16
OLLAMA GGUFqwen35 · 1.94B · BF16
Aug 26, 2026 · Apple M1 Pro
llama-3.1-8b-instruct
LM-STUDIO GGUFllama · 8B · Q8_0
Apr 26, 2026 · AMD Ryzen 5 5500
Global Score
66 vs 81
Hardware Fit
100 vs 100
Quality Score
52 vs 73
Hardware
hf.co/empero-ai/Qw… llama-3.1-8b-instr…
MachineMacBook ProASUS
CPUApple M1 ProAMD Ryzen 5 5500
Cores1012
RAM16 GB31 GB
GPUApple M1 ProNavi 44 [Radeon RX 9060 XT]
OSmacOS 26.6.2Nobara Linux 43
Archarm64x64
Power Modebalancedperformance
Performance
hf.co/empero-ai/Qw… llama-3.1-8b-instr…
Tokens/sec40.235.6
First chunk101 ms52 ms
TTFT101 ms256 ms
Load time2.6 sN/A
Memory usage4.7 GB8.6 GB
Memory %30%28%
HW Fit Score Breakdown
hf.co/empero-ai/Qwen3.8…
Speed
50/50
TTFT
20/20
Memory
30/30
llama-3.1-8b-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
llama-3.1-8b-instruct
Reasoning
13/20
Coding
17/20
Instruction
13/20
Structured
15/15
Math
5/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong 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