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yi-coder:9b

OLLAMA GGUF

llama · 8.8B · Q4_0

Good

Mar 6, 2026 · Apple M4

qwen3.5-2b-mlx

LM-STUDIO MLX

qwen3_5 · 2B · 4bit

Good

Mar 6, 2026 · Apple M4 Pro

Global Score
70 vs 65
Hardware Fit
89 vs 88
Quality Score
62 vs 55

Hardware

yi-coder:9b qwen3.5-2b-mlx
MachineMacBook AirMac mini
CPUApple M4Apple M4 Pro
Cores1014
RAM32 GB64 GB
GPUApple M4Apple M4 Pro
OSmacOS 26.3macOS 15.7.4
Archarm64arm64
Power Modebalancedbalanced

Performance

yi-coder:9b qwen3.5-2b-mlx
Tokens/sec19.448.9
First chunk287 ms4208 ms
TTFT287 ms4.2 s
Load time0.7 sN/A
Memory usage9.6 GB1.6 GB
Memory %30%3%

HW Fit Score Breakdown

yi-coder:9b

Speed
39/50
TTFT
20/20
Memory
30/30

qwen3.5-2b-mlx

Speed
50/50
TTFT
8/20
Memory
30/30

Quality

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

qwen3.5-2b-mlx

Reasoning
10/20
Coding
7/20
Instruction
13/20
Structured
14/15
Math
3/15
Multilingual
8/10
Reasoning: Adequate Coding: Weak Instruction Following: Adequate 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