Back to leaderboard

qwen3.5-0.8b-mlx

LM-STUDIO MLX

qwen3_5 · 0.8B · 4bit

Marginal

Mar 3, 2026 · Apple M4

glm-4.7-flash:bf16

OLLAMA GGUF

deepseek2 · 29.9B · F16

Good

Jun 26, 2026 · Cortex-X925

Global Score
55 vs 76
Hardware Fit
87 vs 73
Quality Score
41 vs 77

Hardware

qwen3.5-0.8b-mlx glm-4.7-flash:bf16
MachineMacBook AirNVIDIA NVIDIA_DGX_Spark
CPUApple M4Cortex-X925
Cores1020
RAM32 GB122 GB
GPUApple M4Device 2e12
OSmacOS 26.3Ubuntu 24.04.4 LTS
Archarm64arm64
Power Modebalancedperformance

Performance

qwen3.5-0.8b-mlx glm-4.7-flash:bf16
Tokens/sec68.225.8
First chunk3268 ms605 ms
TTFT3.3 s605 ms
Load timeN/A44.2 s
Memory usage0.6 GB57.0 GB
Memory %2%47%

HW Fit Score Breakdown

qwen3.5-0.8b-mlx

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

glm-4.7-flash:bf16

Speed
27/50
TTFT
20/20
Memory
26/30

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

glm-4.7-flash:bf16

Reasoning
13/20
Coding
17/20
Instruction
12/20
Structured
15/15
Math
10/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong
View qwen3.5-0.8b-mlx details | View glm-4.7-flash:bf16 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