Contributed byMario AlkaZ.ai (Zhipu) glm-5.2-colibri
Performance benchmark · measured on 27.07.2026 15:23
run-20260727-145955-3c702bPerformance benchmark · Primary metric: Generation-Speed (tok/s) · 5× concurrent
Wie schlägt sich dieser Benchmark mit anderen Modellen?
Hardware
GPU: NVIDIA RTX PRO 6000 Blackwell Workstation Edition · 96 GB VRAM
CPU: AMD Ryzen 9 9950X 16-Core Processor
RAM: 92 GB
Mainboard: ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI
Setup
Runtime: colibri
Quantization: -
Model: glm-5.2-colibri
glm-5.2-colibri on various hardware
All published performance runs of this model – each bubble a variant: position = prefill (X) × generation (Y), bubble size = number of runs. Closer to the top right = faster. ★ Marked gold = this benchmark.
DRVby driver
Economics of this run
Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (5× concurrent). Methodology →
All values above and the charts below take the configured system utilization into account: at X% the system generates only X% of the time, the rest it idles (70 W). Cost per hour drops (more idle), cost per token rises.
Cost over 2 years – electricity only
Cost over 2 years – incl. acquisition (TCO)
Speed vs. tokens per euro
Euro per 1M tokens
Comparison vs. API – economics per benchmark
| glm-5.2-colibriNVIDIA RTX PRO 6000 Blackwell Workstation Edition | |
|---|---|
| Electricity cost (24 mo.) | – |
| Acquisition cost | – |
| Total cost (TCO) | – |
| Generated tokens (24 mo.) | – |
| Token price via API | – |
| Break-even point (days) | – |
| Result (savings / extra cost) | – |
Comparison with up to 3 next-best runs of this model at the same concurrency (at least one on different hardware). Power = GPU TDP + CPU (idle + 15 %) + board (estimated), acquisition = full system (GPU + CPU + board + RAM + PSU), prices = stored market prices.
Mario Alka Administrator
Ich bin Unternehmer, Softwareentwickler und KI-Enthusiast. Seit vielen Jahren entwickle ich Unternehmenssoftware und beschäftige mich inzwischen fast täglich mit lokalen LLMs, KI-Agenten und leistungsfähiger KI-Hardware.
Mit LLM-Benchmark.de möchte ich eine Plattform schaffen, auf der Modelle, GPUs und Agenten objektiv und reproduzierbar miteinander verglichen werden.