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Contributed byMario AlkaZ.ai (Zhipu)

glm-5.2-colibri

Performance benchmark · measured on 27.07.2026 15:12

Benchmark-IDrun-20260727-151333-b860f7
Timebench 3 - Kombi (Prefill + Generation)MoE744BRuntime: colibriQuantisierung: INT4
ℹ
Public note: Native Colibri 1.1.1; Timebench 3 Kombi; HTTP-/Queue-Limit 600 Sekunden. Engine: colibri | Concurrency: 1 | Prefill: 210.62 tok/s | Generation: 0.03 tok/s | Fehler: 0
Generation0,03tok/s
Prefill210,62tok/s
Time to First Token10.088,00ms
Total duration900,00s
Concurrency1parallel
Ranking in the field
1829of 1836 systems

Performance benchmark · Primary metric: Generation-Speed (tok/s) · 1× concurrent

This run is better than 0 % of all comparable systems.
Generation 0,0 tok/s
-100 % vs Ø 77,3
Prefill 210,6 tok/s
-93 % vs Ø 2.839,0
Time to First Token 10.088 ms
-59 % vs Ø 24.818
Distribution in the field0 – 405 tok/s
Ø 77 Median Dieser Lauf

Wie schlägt sich dieser Benchmark mit anderen Modellen?

gpt-oss-20bNVIDIA GeForce RTX 5090 · run-20260724-004608-16af9b
404,6 tok/s
gpt-oss-20bNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260730-035052-9f766a
395,2 tok/s
NVIDIA-Nemotron-3-Nano-4BNVIDIA GeForce RTX 5090 · run-20260728-194135-d456e7
393,5 tok/s
NVIDIA-Nemotron-3-Nano-4BNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260727-181607-bffb11
393,5 tok/s
gpt-oss-20bNVIDIA GeForce RTX 5090 · run-20260724-004607-29bd16
388,9 tok/s
gpt-oss-20bNVIDIA GeForce RTX 5090 · run-20260729-032121-1c779f
388,2 tok/s
gemma-4-E2B-itNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260727-181606-6ea089
378,6 tok/s
gemma-4-E2B-itNVIDIA GeForce RTX 5090 · run-20260728-184455-e8b129
377,6 tok/s
NVIDIA-Nemotron-3-Nano-4B3× 3x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-ac388e
362,3 tok/s
NVIDIA-Nemotron-3-Nano-4B3× 3x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-5e5085
361,4 tok/s
NVIDIA-Nemotron-3-Nano-30B-A3BNVIDIA GeForce RTX 5090 · run-20260729-105335-653788
359,4 tok/s
Nemotron-3-Nano-Omni-30B-A3B-ReasoningNVIDIA GeForce RTX 5090 · run-20260729-105334-2c4905
359,3 tok/s
Nemotron-Cascade-2-30B-A3BNVIDIA GeForce RTX 5090 · run-20260729-105334-44d1e7
359,0 tok/s
Nemotron-3-Nano-Omni-30B-A3B-ReasoningNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260729-032119-4852bf
357,1 tok/s
glm-5.2-colibri this runNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260727-151333-b860f7
0,0 tok/s

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: INT4
Model: glm-5.2-colibri

Configuration

benchmark-konfiguration — run-20260727-151333-b860f7
# LLM-Benchmark Konfiguration # Modell : glm-5.2-colibri # Engine : colibri # Run-ID : run-20260727-151333-b860f7 # GPU : NVIDIA RTX PRO 6000 Blackwell Workstation Edition # CPU : AMD Ryzen 9 9950X 16-Core Processor # RAM : 92 GB bench@llm-benchmark:~$ python3 /usr/local/bin/coli serve \ --model /opt/models/glm52-colibri-int4-g64 \ --host 10.220.4.11 \ --port 8000 \ --model-id glm-5.2-colibri \ --ram 70 \ --auto-tier \ --queue-timeout 600
Engine?Die Inferenz-Software, die das Modell ausliefert (z.B. vLLM oder llama.cpp). Sie bestimmt Geschwindigkeit, unterstuetzte Modellformate und welche Parameter ueberhaupt verfuegbar sind.colibri
Modellalias?Der Name, unter dem das Modell ueber die API angesprochen wird. Genau dieser Wert muss im Request-Feld 'model' stehen.glm-5.2-colibri
Modellpfad?Pfad zur GGUF-Modelldatei, die geladen und ausgeliefert wird./opt/models/glm52-colibri-int4-g64
model-idglm-5.2-colibri
ram70
auto-tieraktiv
queue-timeout600

All benchmarks of this model To leaderboard

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Model comparison

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.

GPUby graphics card

0,00,00,00,00,0140146152157Prefill (tok/s)Generation (tok/s)NVIDIA RTX PRO 6000 Blackwell Workstation Edition - 0,0 tok/s Generation, 149 tok/s Prefill, TTFT 73.893 ms (9 Laufe) | DIESER LAUF★ NVIDIA RTX PRO 6000 B...
★ NVIDIA RTX PRO 6000 Blackwell Workstation Edition 0,0 tok/s this run

CPUby processor

0,00,00,00,00,0140146152157Prefill (tok/s)Generation (tok/s)AMD Ryzen 9 9950X 16-Core Processor - 0,0 tok/s Generation, 149 tok/s Prefill, TTFT 73.893 ms (9 Laufe) | DIESER LAUF★ AMD Ryzen 9 9950X 16-...
★ AMD Ryzen 9 9950X 16-Core Processor 0,0 tok/s this run

MBby mainboard

0,00,00,00,00,0140146152157Prefill (tok/s)Generation (tok/s)ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI - 0,0 tok/s Generation, 149 tok/s Prefill, TTFT 73.893 ms (9 Laufe) | DIESER LAUF★ ASUSTeK COMPUTER INC....
★ ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 0,0 tok/s this run

ENGby engine

0,00,00,00,00,045102160218Prefill (tok/s)Generation (tok/s)unbekannt - 0,0 tok/s Generation, 186 tok/s Prefill, TTFT 10.122 ms (2 Laufe)unbekanntvLLM - 0,0 tok/s Generation, 184 tok/s Prefill, TTFT 10.251 ms (4 Laufe)vLLMcolibri - 0,0 tok/s Generation, 76 tok/s Prefill, TTFT 201.264 ms (3 Laufe) | DIESER LAUF★ colibri
★ colibri 0,0 tok/s this rununbekannt 0,0 tok/svLLM 0,0 tok/s

DRVby driver

0,00,00,00,00,0140146152157Prefill (tok/s)Generation (tok/s)unbekannt - 0,0 tok/s Generation, 149 tok/s Prefill, TTFT 73.893 ms (9 Laufe)unbekannt
unbekannt 0,0 tok/s
💰 Economics

Economics of this run

Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (1× concurrent). Methodology →

⚙️ ConfigurationAll metrics and charts below follow these settings – based on a 24-month runtime.Save to URLReset
⚡ Electricity price EUR/kWh
⚙️ System utilization 100 %
🖥️ Acquisition EUR
🔌 Idle 70 W
⚡ TDP 644 W
☁️ External LLM (API)
Electricity0.30 EUR/kWh
Avg power (incl. idle)644 W estimated (TDP)GPU 600 + CPU 29 + Board 15 W full load
Avg cost / hourEUR 0.19
Electricity / 1M tokensEUR 1,788.19
Token / kWh168
Acquisition (system)EUR 15,248 full priceGPU EUR 13,000 · CPU EUR 649 · Board EUR 499 · RAM EUR 920 · PSU EUR 180
Electricity (2 years)–
TCO (2 years)EUR 18,632
Output tokens (2 years)1.89M
☁️ External LLM (API) – comparison
External LLM cost (2 years)–
Savings vs. external (2 years)–

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 Editionglm-5.2-colibriNVIDIA RTX PRO 6000 Blackwell Workstation Editionglm-5.2-colibriNVIDIA RTX PRO 6000 Blackwell Workstation Editionglm-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.

Contributed by

Mario Alka Administrator

@marioalka

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.