hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16
OLLAMA GGUFqwen35 · 1.94B · BF16
Aug 25, 2026 · Apple M1 Pro
yi-coder:9b
OLLAMA GGUFllama · 8.8B · Q4_0
Mar 6, 2026 · Apple M4
Global Score
76 vs 70
Hardware Fit
100 vs 89
Quality Score
66 vs 62
Hardware
hf.co/empero-ai/Qw… yi-coder:9b
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… yi-coder:9b
Tokens/sec40.319.4
First chunk101 ms287 ms
TTFT101 ms287 ms
Load time2.7 s0.7 s
Memory usage4.5 GB9.6 GB
Memory %28%30%
HW Fit Score Breakdown
hf.co/empero-ai/Qwen3.8…
Speed
50/50
TTFT
20/20
Memory
30/30
yi-coder:9b
Speed
39/50
TTFT
20/20
Memory
30/30
Quality
hf.co/empero-ai/Qwen3.8…
Reasoning
11/20
Coding
10/20
Instruction
12/20
Structured
15/15
Math
8/15
Multilingual
10/10
Reasoning: Adequate Coding: Weak Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong
yi-coder:9b
Reasoning
12/20
Coding
16/20
Instruction
13/20
Structured
7/15
Math
7/15
Multilingual
7/10
Reasoning: Adequate Coding: Strong Instruction Following: Adequate Structured Output: Weak Math: Weak Multilingual: Adequate
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