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Qwen3-VL-30B-A3B-Instruct

Performance benchmark · measured on 29.08.2026 14:09

Benchmark-IDrun-20260829-124021-34de42
Timebench 3 - Kombi (Prefill + Generation)MoE30BRuntime: vLLMQuantisierung: AWQ
ℹ
Public note: NVLink installiert: 2x RTX A6000 ueber NVLink-Bridge (4x NVLink) verbunden.
Generation763,50tok/s
Prefill35.900,13tok/s
Time to First Token986,50ms
Total duration28,91s
Concurrency10parallel
Ranking in the field
247of 1427 systems

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

This run is better than 83 % of all comparable systems.
Generation 763,5 tok/s
+80 % vs Ø 425,3
Prefill 35.900,1 tok/s
+439 % vs Ø 6.659,3
Time to First Token 987 ms
-98 % vs Ø 45.848
Distribution in the field0 – 2.491 tok/s
Ø 425 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-3.5-Lightning-30B-A3BNVIDIA GeForce RTX 3090 Ti · run-20261021-093815-dce558
2.263,7 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× 3x 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× 3x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-0aed86
1.937,7 tok/s
Nemotron-3-Nano-4B3× 3x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-8db0fa
1.911,6 tok/s
Nemotron-3-Nano-4B3× 3x 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× 3x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-034052-26063b
1.835,7 tok/s
Nemotron-3-Nano-4B3× 3x NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-a77046
1.830,3 tok/s
Qwen3-VL-30B-A3B-Instruct this run2× 2x NVIDIA RTX A6000 · run-20260829-124021-34de42
763,5 tok/s

How does this benchmark compare on other GPUs?

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

Hardware

GPU: 2x 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: Qwen3-VL-30B-A3B-Instruct

Configuration

benchmark-konfiguration — run-20260829-124021-34de42
# LLM-Benchmark Konfiguration # Modell : Qwen3-VL-30B-A3B-Instruct # Engine : vLLM # Run-ID : run-20260829-124021-34de42 # GPU : 2x NVIDIA RTX A6000 # CPU : AMD Ryzen Threadripper PRO 7955WX 16-Cores # RAM : 184 GB bench@llm-benchmark:~$ vllm \ --tensor-parallel-size 2 \ --max-model-len 16384 '(2x' RTX A6000 48GB 'NVLink)'
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
Kontextlaenge?Maximale Anzahl Tokens (Eingabe + erzeugte Ausgabe zusammen), die das Modell pro Anfrage verarbeiten kann.16384
Tensor-Parallel?Anzahl GPUs, auf die JEDER einzelne Modell-Layer aufgeteilt wird (Tensor-Parallelitaet). Mehr GPUs = mehr VRAM und meist mehr Speed, aber die Anzahl der Attention-Heads muss durch diesen Wert teilbar sein (z.B. 32 Heads -> nur 1, 2, 4, 8 ... moeglich, NICHT 3).2
Kontext?Groesse des Kontextfensters in Token. 0 = der beim Training verwendete Kontext des Modells.16384
execution_typelocal

All benchmarks of this model To leaderboard

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Model comparison

Qwen3-VL-30B-A3B-Instruct 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

2.1221.5911.0615300,006.96613.93220.898Prefill (tok/s)Generation (tok/s)NVIDIA GeForce RTX 5090 - 1.655,9 tok/s Generation, 9.318 tok/s Prefill, TTFT 3.329 ms (3 Laufe)NVIDIA GeForce RTX 50...NVIDIA RTX PRO 6000 Blackwell Workstation Edition - 1.639,0 tok/s Generation, 17.025 tok/s Prefill, TTFT 1.966 ms (6 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition - 1.505,0 tok/s Generation, 12.905 tok/s Prefill, TTFT 3.350 ms (9 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 3090 Ti - 903,5 tok/s Generation, 5.934 tok/s Prefill, TTFT 5.817 ms (3 Laufe)NVIDIA GeForce RTX 30...AMD Radeon RX 7900 XTX - 301,6 tok/s Generation, 4.865 tok/s Prefill, TTFT 2.767 ms (6 Laufe)AMD Radeon RX 7900 XTXAMD Radeon PRO W7900 Dual Slot - 245,1 tok/s Generation, 4.091 tok/s Prefill, TTFT 3.139 ms (6 Laufe)AMD Radeon PRO W7900 ...AMD Radeon AI PRO R9700 - 233,2 tok/s Generation, 3.718 tok/s Prefill, TTFT 39.315 ms (23 Laufe)AMD Radeon AI PRO R97...AMD Radeon PRO W7800 48GB - 233,0 tok/s Generation, 3.320 tok/s Prefill, TTFT 4.032 ms (7 Laufe)AMD Radeon PRO W7800 ...NVIDIA GeForce RTX 5070 Ti - 154,0 tok/s Generation, 1.182 tok/s Prefill, TTFT 22.532 ms (6 Laufe)NVIDIA GeForce RTX 50...NVIDIA RTX A6000 - 763,5 tok/s Generation, 14.375 tok/s Prefill, TTFT 1.665 ms (36 Laufe) | DIESER LAUF★ NVIDIA RTX A6000
NVIDIA GeForce RTX 5090 1.655,9 tok/sNVIDIA RTX PRO 6000 Blackwell Workstation Edition 1.639,0 tok/sNVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 1.505,0 tok/sNVIDIA GeForce RTX 3090 Ti 903,5 tok/s★ NVIDIA RTX A6000 763,5 tok/s this runAMD Radeon RX 7900 XTX 301,6 tok/sAMD Radeon PRO W7900 Dual Slot 245,1 tok/sAMD Radeon AI PRO R9700 233,2 tok/sAMD Radeon PRO W7800 48GB 233,0 tok/sNVIDIA GeForce RTX 5070 Ti 154,0 tok/s

CPUby processor

2.1081.5811.0545270,006.86413.72720.591Prefill (tok/s)Generation (tok/s)AMD Ryzen 7 5800X3D 8-Core Processor - 1.655,9 tok/s Generation, 9.318 tok/s Prefill, TTFT 3.329 ms (3 Laufe)AMD Ryzen 7 5800X3D 8...AMD Ryzen 9 9950X 16-Core Processor - 1.639,0 tok/s Generation, 17.025 tok/s Prefill, TTFT 1.966 ms (6 Laufe)AMD Ryzen 9 9950X 16-...AMD Ryzen Threadripper PRO 9965WX 24-Cores - 1.505,0 tok/s Generation, 12.905 tok/s Prefill, TTFT 3.350 ms (9 Laufe)AMD Ryzen Threadrippe...AMD Ryzen 9 8945HX with Radeon Graphics - 903,5 tok/s Generation, 5.934 tok/s Prefill, TTFT 5.817 ms (3 Laufe)AMD Ryzen 9 8945HX wi...AMD Ryzen Threadripper PRO 3955WX 16-Cores - 301,6 tok/s Generation, 5.230 tok/s Prefill, TTFT 2.542 ms (3 Laufe)AMD Ryzen Threadrippe...AMD Ryzen Threadripper PRO 5975WX 32-Cores - 245,1 tok/s Generation, 2.888 tok/s Prefill, TTFT 9.592 ms (19 Laufe)AMD Ryzen Threadrippe...AMD Ryzen 3 3100 4-Core Processor - 233,2 tok/s Generation, 4.971 tok/s Prefill, TTFT 2.695 ms (3 Laufe)AMD Ryzen 3 3100 4-Co...Intel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz - 221,6 tok/s Generation, 4.500 tok/s Prefill, TTFT 2.992 ms (3 Laufe)Intel(R) Xeon(R) CPU ...AMD Ryzen Threadripper PRO 7955WX 16-Cores - 763,5 tok/s Generation, 10.502 tok/s Prefill, TTFT 17.073 ms (56 Laufe) | DIESER LAUF★ AMD Ryzen Threadrippe...
AMD Ryzen 7 5800X3D 8-Core Processor 1.655,9 tok/sAMD Ryzen 9 9950X 16-Core Processor 1.639,0 tok/sAMD Ryzen Threadripper PRO 9965WX 24-Cores 1.505,0 tok/sAMD Ryzen 9 8945HX with Radeon Graphics 903,5 tok/s★ AMD Ryzen Threadripper PRO 7955WX 16-Cores 763,5 tok/s this runAMD Ryzen Threadripper PRO 3955WX 16-Cores 301,6 tok/sAMD Ryzen Threadripper PRO 5975WX 32-Cores 245,1 tok/sAMD Ryzen 3 3100 4-Core Processor 233,2 tok/sIntel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz 221,6 tok/s

MBby mainboard

2.1081.5811.0545270,006.84413.68920.533Prefill (tok/s)Generation (tok/s)ASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING - 1.655,9 tok/s Generation, 9.318 tok/s Prefill, TTFT 3.329 ms (3 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI - 1.639,0 tok/s Generation, 17.025 tok/s Prefill, TTFT 1.966 ms (6 Laufe)ASUSTeK COMPUTER INC....Meigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) - 903,5 tok/s Generation, 5.934 tok/s Prefill, TTFT 5.817 ms (3 Laufe)Meigao Innovation Tec...ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI - 301,6 tok/s Generation, 3.207 tok/s Prefill, TTFT 8.631 ms (22 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. ROG STRIX X570-F GAMING - 233,2 tok/s Generation, 4.971 tok/s Prefill, TTFT 2.695 ms (3 Laufe)ASUSTeK COMPUTER INC....Dell Inc. PowerEdge R820 - 221,6 tok/s Generation, 4.500 tok/s Prefill, TTFT 2.992 ms (3 Laufe)Dell Inc. PowerEdge R...ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE - 1.505,0 tok/s Generation, 10.834 tok/s Prefill, TTFT 15.173 ms (65 Laufe) | DIESER LAUF★ ASUSTeK COMPUTER INC....
ASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING 1.655,9 tok/sASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 1.639,0 tok/s★ ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 1.505,0 tok/s this runMeigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) 903,5 tok/sASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 301,6 tok/sASUSTeK COMPUTER INC. ROG STRIX X570-F GAMING 233,2 tok/sDell Inc. PowerEdge R820 221,6 tok/s

ENGby engine

2.1351.6011.0675340,03.4277.63411.84216.049Prefill (tok/s)Generation (tok/s)llama.cpp - 1.655,9 tok/s Generation, 6.921 tok/s Prefill, TTFT 17.959 ms (64 Laufe)llama.cppunbekannt - 89,8 tok/s Generation, 5.705 tok/s Prefill, TTFT 549 ms (7 Laufe)unbekanntvLLM - 1.028,5 tok/s Generation, 13.771 tok/s Prefill, TTFT 2.329 ms (34 Laufe) | DIESER LAUF★ vLLM
llama.cpp 1.655,9 tok/s★ vLLM 1.028,5 tok/s this rununbekannt 89,8 tok/s

DRVby driver

2.1351.6011.0675340,04.5016.5018.50210.502Prefill (tok/s)Generation (tok/s)unbekannt - 1.655,9 tok/s Generation, 9.298 tok/s Prefill, TTFT 12.536 ms (98 Laufe)unbekanntAMD 7.0.0-27-generic - 89,8 tok/s Generation, 5.705 tok/s Prefill, TTFT 549 ms (7 Laufe)AMD 7.0.0-27-generic
unbekannt 1.655,9 tok/sAMD 7.0.0-27-generic 89,8 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 95 W
⚡ TDP 671 W
☁️ External LLM (API)
Electricity0.30 EUR/kWh
Avg power (incl. idle)671 W estimated (TDP)GPU 600 + CPU 46 + Board 25 W full load
Avg cost / hourEUR 0.20
Electricity / 1M tokensEUR 0.073
Token / kWh4.10M
Acquisition (system)EUR 11,454 full priceGPU EUR 6,000 · CPU EUR 1,399 · Board EUR 1,299 · RAM EUR 2,576 · PSU EUR 180
Electricity (2 years)–
TCO (2 years)EUR 14,981
Output tokens (2 years)48.16B
☁️ 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 (95 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

Qwen3-VL-30B-A3B-Instruct2x NVIDIA RTX A6000Qwen3-VL-30B-A3B-InstructNVIDIA GeForce RTX 5090Qwen3-VL-30B-A3B-InstructNVIDIA RTX PRO 6000 Blackwell Workstation EditionQwen3-VL-30B-A3B-Instruct3x NVIDIA RTX PRO 6000 Blackwell Max-Q 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.