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Contributed byMario AlkaQwen (Alibaba)

Qwen3-VL-30B-A3B-Instruct

Performance benchmark · measured on 02.09.2026 08:26

Benchmark-IDrun-20260902-063534-270a3d
Timebench 3 - Kombi (Prefill + Generation)MoE30BRuntime: vLLMQuantisierung: AWQ
Generation54,72tok/s
Prefill2.235,43tok/s
Time to First Token1.089,50ms
Total duration39,61s
Concurrency1parallel
Ranking in the field
723of 1549 systems

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

This run is better than 53 % of all comparable systems.
Generation 54,7 tok/s
-31 % vs Ø 79,0
Prefill 2.235,4 tok/s
-21 % vs Ø 2.837,1
Time to First Token 1.090 ms
-96 % vs Ø 26.963
Distribution in the field0 – 405 tok/s
Ø 79 Median Dieser Lauf

Wie schlägt sich dieser Benchmark mit anderen Modellen?

How does this benchmark compare on other GPUs?

Same model on different hardware · 1× concurrent · Generation (tok/s)

Hardware

GPU: 2x AMD Radeon PRO W7800 48GB · 48 GB VRAM
CPU: AMD Ryzen Threadripper PRO 5975WX 32-Cores
RAM: 62 GB
Mainboard: ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI

Setup

Runtime: vLLM
Quantization: AWQ
Model: Qwen3-VL-30B-A3B-Instruct

Configuration

benchmark-konfiguration — run-20260902-063534-270a3d
# LLM-Benchmark Konfiguration # Modell : Qwen3-VL-30B-A3B-Instruct # Engine : vLLM # Run-ID : run-20260902-063534-270a3d # GPU : 2x AMD Radeon PRO W7800 48GB # CPU : AMD Ryzen Threadripper PRO 5975WX 32-Cores # RAM : 62 GB bench@llm-benchmark:~$ vllm serve \ --tensor-parallel-size 2 \ --max-model-len 16384 '(ROCm' gfx1100, 2x AMD Radeon Pro W7800 '48GB)'
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

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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

2.1351.6011.0675340,006.96613.93220.898Prefill (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...NVIDIA RTX A6000 - 763,5 tok/s Generation, 14.375 tok/s Prefill, TTFT 1.665 ms (36 Laufe)NVIDIA RTX A6000AMD 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 ...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...AMD Radeon AI PRO R9700 - 89,8 tok/s Generation, 3.530 tok/s Prefill, TTFT 44.809 ms (20 Laufe)AMD Radeon AI PRO R97...AMD Radeon PRO W7800 48GB - 233,0 tok/s Generation, 3.940 tok/s Prefill, TTFT 2.809 ms (4 Laufe) | DIESER LAUF★ AMD Radeon PRO W7800 ...
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/sNVIDIA RTX A6000 763,5 tok/sAMD Radeon PRO W7900 Dual Slot 245,1 tok/s★ AMD Radeon PRO W7800 48GB 233,0 tok/s this runNVIDIA GeForce RTX 5070 Ti 154,0 tok/sAMD Radeon AI PRO R9700 89,8 tok/s

CPUby processor

2.1041.5781.0525260,006.85913.71820.578Prefill (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 7955WX 16-Cores - 763,5 tok/s Generation, 10.502 tok/s Prefill, TTFT 17.073 ms (56 Laufe)AMD Ryzen Threadrippe...AMD Ryzen Threadripper PRO 5975WX 32-Cores - 245,1 tok/s Generation, 2.962 tok/s Prefill, TTFT 10.329 ms (16 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/sAMD Ryzen Threadripper PRO 7955WX 16-Cores 763,5 tok/s★ AMD Ryzen Threadripper PRO 5975WX 32-Cores 245,1 tok/s this run

MBby mainboard

2.1041.5781.0525260,006.85913.71820.578Prefill (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....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)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 - 245,1 tok/s Generation, 2.962 tok/s Prefill, TTFT 10.329 ms (16 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/sASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 1.505,0 tok/sMeigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) 903,5 tok/s★ ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 245,1 tok/s this run

ENGby engine

2.1351.6011.0675340,03.1657.91112.65717.403Prefill (tok/s)Generation (tok/s)llama.cpp - 1.655,9 tok/s Generation, 7.252 tok/s Prefill, TTFT 20.449 ms (55 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, 14.863 tok/s Prefill, TTFT 2.006 ms (31 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

2.1351.6011.0675340,04.3336.6789.02311.367Prefill (tok/s)Generation (tok/s)unbekannt - 1.655,9 tok/s Generation, 9.995 tok/s Prefill, TTFT 13.801 ms (86 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 (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 10 W
⚡ TDP 530 W
☁️ External LLM (API)
Electricity0.30 EUR/kWh
Avg power (incl. idle)530 W estimated (TDP)GPU 520 + Board 10 W full load
Avg cost / hourEUR 0.16
Electricity / 1M tokensEUR 0.81
Token / kWh371.68K
Acquisition (system)EUR 8,172 partial priceGPU EUR 5,616 · CPU EUR 1,880 · RAM EUR 496 · PSU EUR 180
Electricity (2 years)
TCO (2 years)EUR 10,958
Output tokens (2 years)3.45B
☁️ 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 (10 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 AMD Radeon PRO W7800 48GBQwen3-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.