vicuna:13b

OLLAMA GGUF

llama · 13B · Q4_0

Marginal

Mar 1, 2026 · Apple M4

qwen3.5-0.8b-mlx

LM-STUDIO MLX

qwen3_5 · 0.8B · 4bit

Marginal

Mar 6, 2026 · Apple M4 Pro

Global Score

59 vs 53

Hardware Fit

84 vs 89

Quality Score

48 vs 38

Hardware

vicuna:13b qwen3.5-0.8b-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

vicuna:13b qwen3.5-0.8b-mlx

Tokens/sec13.452.9

First chunkN/A4013 ms

TTFT438 ms4.0 s

Load time0.6 sN/A

Memory usage10.3 GB0.6 GB

Memory %32%1%

HW Fit Score Breakdown

vicuna:13b

Speed

24/50

TTFT

30/20

Memory

30/30

qwen3.5-0.8b-mlx

Speed

50/50

TTFT

9/20

Memory

30/30

Quality

vicuna:13b

Reasoning

7/20

Coding

5/20

Instruction

12/20

Structured

13/15

Math

3/15

Multilingual

8/10

Reasoning: Weak Coding: Weak Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Strong

qwen3.5-0.8b-mlx

Reasoning

7/20

Coding

2/20

Instruction

12/20

Structured

10/15

Math

2/15

Multilingual

5/10

Reasoning: Weak Coding: Poor Instruction Following: Adequate Structured Output: Adequate Math: Poor Multilingual: Adequate

View vicuna:13b 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