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glm-4.6v-flash

LM-STUDIO GGUF

glm4 · Q4_K_S

Good

Apr 21, 2026 · Apple M2 Max

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

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 22, 2026 · Apple M1 Pro

Global Score
65 vs 66
Hardware Fit
88 vs 100
Quality Score
55 vs 52

Hardware

glm-4.6v-flash hf.co/empero-ai/Qw…
MachineMac StudioMacBook Pro
CPUApple M2 MaxApple M1 Pro
Cores1210
RAM96 GB16 GB
GPUApple M2 MaxApple M1 Pro
OSmacOS 26.1macOS 26.6.2
Archarm64arm64
Power Modebalancedbalanced

Performance

glm-4.6v-flash hf.co/empero-ai/Qw…
Tokens/sec49.940.2
First chunk27 ms325 ms
TTFT3.7 s325 ms
Load time2.7 s3.1 s
Memory usage0.0 GB4.7 GB
Memory %0%30%

HW Fit Score Breakdown

glm-4.6v-flash

Speed
50/50
TTFT
8/20
Memory
30/30

hf.co/empero-ai/Qwen3.8…

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

Quality

glm-4.6v-flash

Reasoning
0/20
Coding
16/20
Instruction
12/20
Structured
2/15
Math
15/15
Multilingual
10/10
Reasoning: Poor Coding: Strong Instruction Following: Adequate Structured Output: Poor Math: Strong 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
View glm-4.6v-flash 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