Back to leaderboard

glm-4.7-flash:q4_K_M

OLLAMA GGUF

glm4moelite · 29.9B · Q4_K_M

Excellent

Mar 7, 2026 · Intel Core™ i5-14600KF

hf.co/empero-ai/Qwen3.8-4B-Distill-GGUF:Q4_K_M

OLLAMA GGUF

qwen35 · 4.33B · unknown

Good

Aug 28, 2026 · Apple M4

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

Hardware

glm-4.7-flash:q4_K_M hf.co/empero-ai/Qw…
MachineASUSMacBook Pro
CPUIntel Core™ i5-14600KFApple M4
Cores2010
RAM32 GB16 GB
GPUNVIDIA GeForce RTX 4070 Ti SUPERApple M4
OSMicrosoft Windows 11 Famille 10.0.26200macOS 26.6.1
Archx64arm64
Power Modebalancedbalanced

Performance

glm-4.7-flash:q4_K_M hf.co/empero-ai/Qw…
Tokens/sec35.126.5
First chunk440 ms447 ms
TTFT440 ms447 ms
Load time11.6 s3.3 s
Memory usage18.4 GB4.8 GB
Memory %58%30%

HW Fit Score Breakdown

glm-4.7-flash:q4_K_M

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

hf.co/empero-ai/Qwen3.8…

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

Quality

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

hf.co/empero-ai/Qwen3.8…

Reasoning
18/20
Coding
14/20
Instruction
4/20
Structured
1/15
Math
15/15
Multilingual
0/10
Reasoning: Strong Coding: Adequate Instruction Following: Poor Structured Output: Poor Math: Strong Multilingual: Poor
View glm-4.7-flash:q4_K_M details | View hf.co/empero-ai/Qw… 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