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hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 23, 2026 · Apple M1 Pro

glm-4.7-flash:q4_K_M

OLLAMA GGUF

glm4moelite · 29.9B · Q4_K_M

Excellent

Mar 7, 2026 · Intel Core™ i5-14600KF

Global Score
66 vs 81
Hardware Fit
100 vs 89
Quality Score
52 vs 77

Hardware

hf.co/empero-ai/Qw… glm-4.7-flash:q4_K_M
MachineMacBook ProASUS
CPUApple M1 ProIntel Core™ i5-14600KF
Cores1020
RAM16 GB32 GB
GPUApple M1 ProNVIDIA GeForce RTX 4070 Ti SUPER
OSmacOS 26.6.2Microsoft Windows 11 Famille 10.0.26200
Archarm64x64
Power Modebalancedbalanced

Performance

hf.co/empero-ai/Qw… glm-4.7-flash:q4_K_M
Tokens/sec40.435.1
First chunk93 ms440 ms
TTFT93 ms440 ms
Load time2.7 s11.6 s
Memory usage4.7 GB18.4 GB
Memory %30%58%

HW Fit Score Breakdown

hf.co/empero-ai/Qwen3.8…

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

glm-4.7-flash:q4_K_M

Speed
49/50
TTFT
20/20
Memory
20/30

Quality

hf.co/empero-ai/Qwen3.8…

Reasoning
15/20
Coding
9/20
Instruction
8/20
Structured
1/15
Math
15/15
Multilingual
4/10
Reasoning: Adequate Coding: Weak Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Weak

glm-4.7-flash:q4_K_M

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 hf.co/empero-ai/Qw… details | View glm-4.7-flash:q4_K_M 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