Created bymario-alka.dePowered bygodcore.denoob2claw.detricoma.de
Contributed byMario AlkaQwen (Alibaba)

Qwen3.5-35B-A3B

Performance benchmark · measured on 26.08.2026 17:23

Benchmark-IDrun-20260826-152552-6ef37d
Timebench 3 - Kombi (Prefill + Generation)MoE35BRuntime: llama.cppQuantisierung: Q4_K_M
Generation143,98tok/s
Prefill3.575,92tok/s
Time to First Token540,00ms
Total duration15,31s
Concurrency1parallel
Ranking in the field
208of 1220 systems

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

This run is better than 83 % of all comparable systems.
Generation 144,0 tok/s
+91 % vs Ø 75,3
Prefill 3.575,9 tok/s
+49 % vs Ø 2.399,5
Time to First Token 540 ms
-98 % vs Ø 33.995
Distribution in the field0 – 405 tok/s
Ø 75 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: 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: llama.cpp
Quantization: Q4_K_M
Model: Qwen3.5-35B-A3B

Configuration

benchmark-konfiguration — run-20260826-152552-6ef37d
# LLM-Benchmark Konfiguration # Modell : Qwen3.5-35B-A3B # Engine : llama.cpp # Run-ID : run-20260826-152552-6ef37d # GPU : NVIDIA RTX A6000 # CPU : AMD Ryzen Threadripper PRO 7955WX 16-Cores # RAM : 184 GB bench@llm-benchmark:~$ /home/godcore/llama.cpp/build/bin/llama-server \ -m Qwen_Qwen3.5-35B-A3B-Q4_K_M.gguf \ -ngl 999 \ -fa on \ -c 49152 \ -np 12
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.llamacpp
Kontextlaenge?Maximale Anzahl Tokens (Eingabe + erzeugte Ausgabe zusammen), die das Modell pro Anfrage verarbeiten kann.49152
Modellpfad?Pfad zur GGUF-Modelldatei, die geladen und ausgeliefert wird.Qwen_Qwen3.5-35B-A3B-Q4_K_M.gguf
GPU-Layer?Anzahl der auf die GPU ausgelagerten Modell-Layer. Hoeher = mehr VRAM und schneller; der Rest laeuft auf der CPU. 999 = alles auf GPU.999
faon
Kontext?Groesse des Kontextfensters in Token. 0 = der beim Training verwendete Kontext des Modells.49152
np12

All benchmarks of this model To leaderboard

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Model comparison

Qwen3.5-35B-A3B 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

1.9671.4759844920,005.26410.52815.792Prefill (tok/s)Generation (tok/s)NVIDIA RTX PRO 6000 Blackwell Workstation Edition - 1.520,4 tok/s Generation, 12.809 tok/s Prefill, TTFT 2.176 ms (6 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 5090 - 1.416,7 tok/s Generation, 5.541 tok/s Prefill, TTFT 3.907 ms (3 Laufe)NVIDIA GeForce RTX 50...NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition - 1.398,4 tok/s Generation, 6.870 tok/s Prefill, TTFT 4.115 ms (11 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 3090 Ti - 866,1 tok/s Generation, 3.371 tok/s Prefill, TTFT 6.651 ms (3 Laufe)NVIDIA GeForce RTX 30...AMD Radeon AI PRO R9700 - 220,5 tok/s Generation, 2.194 tok/s Prefill, TTFT 25.070 ms (27 Laufe)AMD Radeon AI PRO R97...AMD Radeon PRO W7900 Dual Slot - 212,5 tok/s Generation, 2.015 tok/s Prefill, TTFT 5.888 ms (12 Laufe)AMD Radeon PRO W7900 ...NVIDIA GeForce RTX 5070 Ti - 142,2 tok/s Generation, 508 tok/s Prefill, TTFT 31.910 ms (6 Laufe)NVIDIA GeForce RTX 50...NVIDIA GB10 (DGX Spark) - 46,9 tok/s Generation, 3.713 tok/s Prefill, TTFT 537 ms (1 Lauf)NVIDIA GB10 (DGX Spar...NVIDIA RTX A6000 - 304,5 tok/s Generation, 4.059 tok/s Prefill, TTFT 2.420 ms (3 Laufe) | DIESER LAUF★ NVIDIA RTX A6000
NVIDIA RTX PRO 6000 Blackwell Workstation Edition 1.520,4 tok/sNVIDIA GeForce RTX 5090 1.416,7 tok/sNVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 1.398,4 tok/sNVIDIA GeForce RTX 3090 Ti 866,1 tok/s★ NVIDIA RTX A6000 304,5 tok/s this runAMD Radeon AI PRO R9700 220,5 tok/sAMD Radeon PRO W7900 Dual Slot 212,5 tok/sNVIDIA GeForce RTX 5070 Ti 142,2 tok/sNVIDIA GB10 (DGX Spark) 46,9 tok/s

CPUby processor

1.9671.4759844920,005.20410.40715.611Prefill (tok/s)Generation (tok/s)AMD Ryzen 9 9950X 16-Core Processor - 1.520,4 tok/s Generation, 12.809 tok/s Prefill, TTFT 2.176 ms (6 Laufe)AMD Ryzen 9 9950X 16-...AMD Ryzen 7 5800X3D 8-Core Processor - 1.416,7 tok/s Generation, 5.541 tok/s Prefill, TTFT 3.907 ms (3 Laufe)AMD Ryzen 7 5800X3D 8...AMD Ryzen Threadripper PRO 9965WX 24-Cores - 1.398,4 tok/s Generation, 6.870 tok/s Prefill, TTFT 4.115 ms (11 Laufe)AMD Ryzen Threadrippe...AMD Ryzen 9 8945HX with Radeon Graphics - 866,1 tok/s Generation, 3.371 tok/s Prefill, TTFT 6.651 ms (3 Laufe)AMD Ryzen 9 8945HX wi...AMD Ryzen Threadripper PRO 5975WX 32-Cores - 212,5 tok/s Generation, 1.513 tok/s Prefill, TTFT 14.562 ms (18 Laufe)AMD Ryzen Threadrippe...NVIDIA Grace - 46,9 tok/s Generation, 3.713 tok/s Prefill, TTFT 537 ms (1 Lauf)NVIDIA GraceAMD Ryzen Threadripper PRO 7955WX 16-Cores - 304,5 tok/s Generation, 2.380 tok/s Prefill, TTFT 22.805 ms (30 Laufe) | DIESER LAUF★ AMD Ryzen Threadrippe...
AMD Ryzen 9 9950X 16-Core Processor 1.520,4 tok/sAMD Ryzen 7 5800X3D 8-Core Processor 1.416,7 tok/sAMD Ryzen Threadripper PRO 9965WX 24-Cores 1.398,4 tok/sAMD Ryzen 9 8945HX with Radeon Graphics 866,1 tok/s★ AMD Ryzen Threadripper PRO 7955WX 16-Cores 304,5 tok/s this runAMD Ryzen Threadripper PRO 5975WX 32-Cores 212,5 tok/sNVIDIA Grace 46,9 tok/s

MBby mainboard

1.9671.4759844920,005.20410.40715.611Prefill (tok/s)Generation (tok/s)ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI - 1.520,4 tok/s Generation, 12.809 tok/s Prefill, TTFT 2.176 ms (6 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING - 1.416,7 tok/s Generation, 5.541 tok/s Prefill, TTFT 3.907 ms (3 Laufe)ASUSTeK COMPUTER INC....Meigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) - 866,1 tok/s Generation, 3.371 tok/s Prefill, TTFT 6.651 ms (3 Laufe)Meigao Innovation Tec...ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI - 212,5 tok/s Generation, 1.513 tok/s Prefill, TTFT 14.562 ms (18 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. GX10 - 46,9 tok/s Generation, 3.713 tok/s Prefill, TTFT 537 ms (1 Lauf)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE - 1.398,4 tok/s Generation, 3.585 tok/s Prefill, TTFT 17.790 ms (41 Laufe) | DIESER LAUF★ ASUSTeK COMPUTER INC....
ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 1.520,4 tok/sASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING 1.416,7 tok/s★ ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 1.398,4 tok/s this runMeigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) 866,1 tok/sASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 212,5 tok/sASUSTeK COMPUTER INC. GX10 46,9 tok/s

ENGby engine

1.9611.4719804900,01.4313.7196.0078.296Prefill (tok/s)Generation (tok/s)vLLM - 1.028,6 tok/s Generation, 7.075 tok/s Prefill, TTFT 6.086 ms (11 Laufe)vLLMunbekannt - 78,5 tok/s Generation, 2.652 tok/s Prefill, TTFT 858 ms (5 Laufe)unbekanntllama.cpp - 1.520,4 tok/s Generation, 3.401 tok/s Prefill, TTFT 17.242 ms (56 Laufe) | DIESER LAUF★ llama.cpp
★ llama.cpp 1.520,4 tok/s this runvLLM 1.028,6 tok/sunbekannt 78,5 tok/s

DRVby driver

1.9671.4759844920,02.1672.9423.7184.493Prefill (tok/s)Generation (tok/s)unbekannt - 1.520,4 tok/s Generation, 4.008 tok/s Prefill, TTFT 15.636 ms (66 Laufe)unbekanntAMD 7.0.0-27-generic - 78,5 tok/s Generation, 2.652 tok/s Prefill, TTFT 858 ms (5 Laufe)AMD 7.0.0-27-genericNVIDIA 590.48.01 / CUDA 13.1 - 46,9 tok/s Generation, 3.713 tok/s Prefill, TTFT 537 ms (1 Lauf)NVIDIA 590.48.01 / CU...
unbekannt 1.520,4 tok/sAMD 7.0.0-27-generic 78,5 tok/sNVIDIA 590.48.01 / CUDA 13.1 46,9 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 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 0.041
Token / kWh7.30M
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)9.08B
☁️ 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

Qwen3.5-35B-A3BNVIDIA RTX A6000Qwen3.5-35B-A3BNVIDIA GeForce RTX 5090Qwen3.5-35B-A3BNVIDIA RTX PRO 6000 Blackwell Workstation EditionQwen3.5-35B-A3B3x 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.