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Contributed byMario AlkaQwen (Alibaba)

Qwen2.5-32B-Instruct-AWQ

Performance benchmark · measured on 26.08.2026 23:34

Benchmark-IDrun-20260826-215014-c6b10c
Timebench 3 - Kombi (Prefill + Generation)Dense32BRuntime: vLLMQuantisierung: AWQ
Generation191,84tok/s
Prefill3.436,58tok/s
Time to First Token9.775,50ms
Total duration127,61s
Concurrency10parallel
Ranking in the field
496of 907 systems

Performance benchmark · Primary metric: Generation-Speed (tok/s) · 10× concurrent

This run is better than 45 % of all comparable systems.
Generation 191,8 tok/s
-59 % vs Ø 468,3
Prefill 3.436,6 tok/s
-33 % vs Ø 5.110,4
Time to First Token 9.776 ms
-83 % vs Ø 58.580
Distribution in the field0 – 2.491 tok/s
Ø 468 Median Dieser Lauf

Wie schlägt sich dieser Benchmark mit anderen Modellen?

gemma-4-E2B-itNVIDIA GeForce RTX 5090 · run-20260728-184455-e28775
2.491,2 tok/s
gemma-4-E2B-itNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260727-181606-b37ed9
2.414,4 tok/s
Nemotron-3-Nano-4BNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260727-181607-4cca42
2.182,7 tok/s
gemma-4-E2B-it3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-184456-d87c73
2.143,6 tok/s
gpt-oss-20bNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260730-035052-9c966e
1.995,4 tok/s
gpt-oss-20bNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260728-140954-8007c4
1.993,5 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-0aed86
1.937,7 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-8db0fa
1.911,6 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260727-181606-e0eafd
1.897,0 tok/s
gpt-oss-20bNVIDIA GeForce RTX 5090 · run-20260729-032121-7c961d
1.890,7 tok/s
Nemotron-3-Nano-4BNVIDIA GeForce RTX 5090 · run-20260728-194135-2ed9dd
1.878,7 tok/s
gpt-oss-20b3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-034052-26063b
1.835,7 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-a77046
1.830,3 tok/s
gpt-oss-20b3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260729-032121-c6e7e0
1.819,5 tok/s
Qwen2.5-32B-Instruct-AWQ this runNVIDIA RTX A6000 · run-20260826-215014-c6b10c
191,8 tok/s

How does this benchmark compare on other GPUs?

Same model on different hardware · 10× concurrent · Generation (tok/s)

Hardware

GPU: NVIDIA RTX A6000 · 48 GB VRAM
CPU: AMD Ryzen Threadripper PRO 7955WX 16-Cores
RAM: 184 GB
Mainboard: ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE

Setup

Runtime: vLLM
Quantization: AWQ
Model: Qwen2.5-32B-Instruct-AWQ

Configuration

benchmark-konfiguration — run-20260826-215014-c6b10c
# LLM-Benchmark Konfiguration # Modell : Qwen2.5-32B-Instruct-AWQ # Engine : vLLM # Run-ID : run-20260826-215014-c6b10c # GPU : NVIDIA RTX A6000 # CPU : AMD Ryzen Threadripper PRO 7955WX 16-Cores # RAM : 184 GB bench@llm-benchmark:~$ vllm serve \ --model Qwen2.5-32B-Instruct
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.vllm
Modellalias?Der Name, unter dem das Modell ueber die API angesprochen wird. Genau dieser Wert muss im Request-Feld 'model' stehen.Qwen2.5-32B-Instruct

All benchmarks of this model To leaderboard

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Model comparison

Qwen2.5-32B-Instruct-AWQ 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

6594943291650,001.8803.7615.641Prefill (tok/s)Generation (tok/s)NVIDIA RTX PRO 6000 Blackwell Workstation Edition - 510,3 tok/s Generation, 4.510 tok/s Prefill, TTFT 5.988 ms (6 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 5090 - 473,9 tok/s Generation, 4.532 tok/s Prefill, TTFT 9.919 ms (3 Laufe)NVIDIA GeForce RTX 50...NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition - 412,6 tok/s Generation, 4.568 tok/s Prefill, TTFT 11.783 ms (9 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 3090 Ti - 223,8 tok/s Generation, 2.049 tok/s Prefill, TTFT 20.233 ms (6 Laufe)NVIDIA GeForce RTX 30...AMD Radeon PRO W7900 Dual Slot - 89,6 tok/s Generation, 1.013 tok/s Prefill, TTFT 13.903 ms (3 Laufe)AMD Radeon PRO W7900 ...NVIDIA GeForce RTX 5070 Ti - 45,0 tok/s Generation, 619 tok/s Prefill, TTFT 95.102 ms (3 Laufe)NVIDIA GeForce RTX 50...AMD Radeon AI PRO R9700 - 22,3 tok/s Generation, 127 tok/s Prefill, TTFT 138.392 ms (10 Laufe)AMD Radeon AI PRO R97...NVIDIA RTX A6000 - 191,8 tok/s Generation, 2.497 tok/s Prefill, TTFT 5.690 ms (3 Laufe) | DIESER LAUF★ NVIDIA RTX A6000
NVIDIA RTX PRO 6000 Blackwell Workstation Edition 510,3 tok/sNVIDIA GeForce RTX 5090 473,9 tok/sNVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 412,6 tok/sNVIDIA GeForce RTX 3090 Ti 223,8 tok/s★ NVIDIA RTX A6000 191,8 tok/s this runAMD Radeon PRO W7900 Dual Slot 89,6 tok/sNVIDIA GeForce RTX 5070 Ti 45,0 tok/sAMD Radeon AI PRO R9700 22,3 tok/s

CPUby processor

6464843231610,001.8483.6955.543Prefill (tok/s)Generation (tok/s)AMD Ryzen 9 9950X 16-Core Processor - 510,3 tok/s Generation, 4.510 tok/s Prefill, TTFT 5.988 ms (6 Laufe)AMD Ryzen 9 9950X 16-...AMD Ryzen 7 5800X3D 8-Core Processor - 473,9 tok/s Generation, 4.532 tok/s Prefill, TTFT 9.919 ms (3 Laufe)AMD Ryzen 7 5800X3D 8...AMD Ryzen Threadripper PRO 9965WX 24-Cores - 412,6 tok/s Generation, 4.568 tok/s Prefill, TTFT 11.783 ms (9 Laufe)AMD Ryzen Threadrippe...AMD Ryzen 9 8945HX with Radeon Graphics - 223,8 tok/s Generation, 2.049 tok/s Prefill, TTFT 20.233 ms (6 Laufe)AMD Ryzen 9 8945HX wi...AMD Ryzen Threadripper PRO 5975WX 32-Cores - 89,6 tok/s Generation, 816 tok/s Prefill, TTFT 54.502 ms (6 Laufe)AMD Ryzen Threadrippe...AMD Ryzen Threadripper PRO 7955WX 16-Cores - 191,8 tok/s Generation, 674 tok/s Prefill, TTFT 107.769 ms (13 Laufe) | DIESER LAUF★ AMD Ryzen Threadrippe...
AMD Ryzen 9 9950X 16-Core Processor 510,3 tok/sAMD Ryzen 7 5800X3D 8-Core Processor 473,9 tok/sAMD Ryzen Threadripper PRO 9965WX 24-Cores 412,6 tok/sAMD Ryzen 9 8945HX with Radeon Graphics 223,8 tok/s★ AMD Ryzen Threadripper PRO 7955WX 16-Cores 191,8 tok/s this runAMD Ryzen Threadripper PRO 5975WX 32-Cores 89,6 tok/s

MBby mainboard

6464843231610,001.8243.6495.473Prefill (tok/s)Generation (tok/s)ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI - 510,3 tok/s Generation, 4.510 tok/s Prefill, TTFT 5.988 ms (6 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING - 473,9 tok/s Generation, 4.532 tok/s Prefill, TTFT 9.919 ms (3 Laufe)ASUSTeK COMPUTER INC....Meigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) - 223,8 tok/s Generation, 2.049 tok/s Prefill, TTFT 20.233 ms (6 Laufe)Meigao Innovation Tec...ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI - 89,6 tok/s Generation, 816 tok/s Prefill, TTFT 54.502 ms (6 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE - 412,6 tok/s Generation, 2.267 tok/s Prefill, TTFT 68.502 ms (22 Laufe) | DIESER LAUF★ ASUSTeK COMPUTER INC....
ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 510,3 tok/sASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING 473,9 tok/s★ ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 412,6 tok/s this runMeigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) 223,8 tok/sASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 89,6 tok/s

ENGby engine

5695304924544161.9372.5863.2363.886Prefill (tok/s)Generation (tok/s)llama.cpp - 474,0 tok/s Generation, 2.348 tok/s Prefill, TTFT 53.942 ms (37 Laufe)llama.cppvLLM - 510,3 tok/s Generation, 3.475 tok/s Prefill, TTFT 4.216 ms (6 Laufe) | DIESER LAUF★ vLLM
★ vLLM 510,3 tok/s this runllama.cpp 474,0 tok/s

DRVby driver

5615365104854592.3552.4552.5552.655Prefill (tok/s)Generation (tok/s)unbekannt - 510,3 tok/s Generation, 2.505 tok/s Prefill, TTFT 47.003 ms (43 Laufe)unbekannt
unbekannt 510,3 tok/s
💰 Economics

Economics of this run

Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (10× 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 65 W
⚡ TDP 71 W
☁️ External LLM (API)
Electricity0.30 EUR/kWh
Avg power (incl. idle)71 W missingCPU 46 + Board 25 W full load
Avg cost / hourEUR 0.021
Electricity / 1M tokensEUR 0.031
Token / kWh9.73M
Acquisition (system)EUR 8,394 full priceGPU EUR 3,000 · CPU EUR 1,399 · Board EUR 1,299 · RAM EUR 2,576 · PSU EUR 120
Electricity (2 years)
TCO (2 years)EUR 8,767
Output tokens (2 years)12.10B
☁️ External LLM (API) – comparison
External LLM cost (2 years)
Savings vs. external (2 years)
No power draw measured – values estimated from GPU TDP + CPU (idle + 15 %) + board.

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 (65 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

Qwen2.5-32B-Instruct-AWQNVIDIA RTX A6000Qwen2.5-32B-Instruct-AWQNVIDIA RTX PRO 6000 Blackwell Workstation EditionQwen2.5-32B-Instruct-AWQNVIDIA RTX PRO 6000 Blackwell Workstation EditionQwen2.5-32B-Instruct-AWQNVIDIA GeForce RTX 5090
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.