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mlx-community/meta-llama-3.1-8b-instruct

LM-STUDIO MLX

llama · 8B · 4bit

Good

Mar 5, 2026 · Apple M4 Pro

qwen3.5-0.8b-mlx

LM-STUDIO MLX

qwen3_5 · 0.8B · 4bit

Marginal

Mar 3, 2026 · Apple M4

Global Score
77 vs 55
Hardware Fit
100 vs 87
Quality Score
67 vs 41

Hardware

mlx-community/meta… qwen3.5-0.8b-mlx
MachineMac miniMacBook Air
CPUApple M4 ProApple M4
Cores1410
RAM64 GB32 GB
GPUApple M4 ProApple M4
OSmacOS 15.7.4macOS 26.3
Archarm64arm64
Power Modebalancedbalanced

Performance

mlx-community/meta… qwen3.5-0.8b-mlx
Tokens/sec54.368.2
First chunk277 ms3268 ms
TTFT277 ms3.3 s
Load timeN/AN/A
Memory usage4.2 GB0.6 GB
Memory %7%2%

HW Fit Score Breakdown

mlx-community/meta-llam…

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

qwen3.5-0.8b-mlx

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

Quality

mlx-community/meta-llam…

Reasoning
11/20
Coding
14/20
Instruction
14/20
Structured
15/15
Math
4/15
Multilingual
9/10
Reasoning: Adequate Coding: Adequate Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Strong

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

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