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qwen3.5-0.8b-mlx

LM-STUDIO MLX

qwen3_5 · 0.8B · 4bit

Marginal

Mar 3, 2026 · Apple M4

vicuna:7b

OLLAMA GGUF

llama · 7B · Q4_0

Marginal

Mar 1, 2026 · Apple M4

Global Score
55 vs 59
Hardware Fit
87 vs 97
Quality Score
41 vs 43

Hardware

qwen3.5-0.8b-mlx vicuna:7b
MachineMacBook AirMacBook Air
CPUApple M4Apple M4
Cores1010
RAM32 GB32 GB
GPUApple M4Apple M4
OSmacOS 26.3macOS 26.3
Archarm64arm64
Power Modebalancedbalanced

Performance

qwen3.5-0.8b-mlx vicuna:7b
Tokens/sec68.223.4
First chunk3268 msN/A
TTFT3.3 s242 ms
Load timeN/A0.4 s
Memory usage0.6 GB5.8 GB
Memory %2%18%

HW Fit Score Breakdown

qwen3.5-0.8b-mlx

Speed
50/50
TTFT
13/20
Memory
24/30

vicuna:7b

Speed
37/50
TTFT
30/20
Memory
30/30

Quality

qwen3.5-0.8b-mlx

Reasoning
8/20
Coding
1/20
Instruction
12/20
Structured
12/15
Math
3/15
Multilingual
5/10
Reasoning: Weak Coding: Poor Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Adequate

vicuna:7b

Reasoning
8/20
Coding
4/20
Instruction
10/20
Structured
12/15
Math
2/15
Multilingual
7/10
Reasoning: Weak Coding: Poor Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Adequate

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