glm-4.7-flash:latest

glm4moelite · 29.9B · Q4_K_M

AZW GTR Pro (AMD RYZEN AI MAX+ 395)

125 GB · Ubuntu 24.04.4 LTS

Tested on March 22, 2026

Top 14% Compare

Global Score

82 /100

Excellent

Hardware Fit

94/100

Quality

77/100

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Ollama

ollama pull glm-4.7-flash:latest

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ollama.com/library/glm-4.7-flash

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GGUF versions & quantizations

Hardware

Machine: AZW GTR Pro
CPU: AMD RYZEN AI MAX+ 395
Cores: 32 threads (16 cores)
Frequency: 3 GHz
RAM: 125 GB
GPU: Radeon 8060S
OS: Ubuntu 24.04.4 LTS
Arch: x64
Power Mode: performance

Performance

Tokens/sec Tokens generated per second — higher is better: 47.6
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.3
First chunk latency Delay before the first streamed chunk arrives from runtime: 200 ms
Time to first token How fast the model starts responding — lower is better: 200 ms
Load time Time to load the model into memory before inference: 7.3 s
Memory usage RAM consumed during inference — percentage of total system memory: 37.7 GB (30%)
Total tokens Total number of tokens generated across all benchmark prompts: 1024

Score breakdown

Speed

44/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

13/20

Coding

17/20

Instruction following

12/20

Structured output

15/15

Math

10/15

Multilingual

10/10

Category levels

Reasoning: Adequate Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Adequate Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: HIGH-END
Result hash: e32e131aa80efc34cc5d09b2bbb780c890d63fa6b2e3237e2a8174cb86ad0466

Interpretation

Hardware fit: 94/100. Overall suitability: EXCELLENT (Global 82/100). Category profile: Reasoning: Adequate, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Bench Environment

Thermal: nominal CPU load: avg 3% (peak 4%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest