glm-4.7-flash:q4_K_M
OLLAMA GGUFglm4moelite · 29.9B · Q4_K_M
Mar 7, 2026 · Intel Core™ i5-14600KF
hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16
OLLAMA GGUFqwen35 · 1.94B · BF16
Aug 22, 2026 · Apple M1 Pro
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 M1 Pro
Cores2010
RAM32 GB16 GB
GPUNVIDIA GeForce RTX 4070 Ti SUPERApple M1 Pro
OSMicrosoft Windows 11 Famille 10.0.26200macOS 26.6.2
Archx64arm64
Power Modebalancedbalanced
Performance
glm-4.7-flash:q4_K_M hf.co/empero-ai/Qw…
Tokens/sec35.140.2
First chunk440 ms325 ms
TTFT440 ms325 ms
Load time11.6 s3.1 s
Memory usage18.4 GB4.7 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
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
Run yours and compare
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest