# LLM-Benchmark Konfiguration # Modell : Nemotron-3-Nano-4B # Engine : vLLM # Run-ID : run-20260829-095458-86d0b5 # 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

All benchmarks of this model To leaderboard

Model comparison

Nemotron-3-Nano-4B 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

NVIDIA RTX PRO 6000 Blackwell Workstation Edition 2.182,7 tok/sNVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 1.937,7 tok/sNVIDIA GeForce RTX 5090 1.878,7 tok/s★ NVIDIA RTX A6000 1.485,1 tok/s this runNVIDIA GeForce RTX 5070 Ti 1.197,0 tok/sNVIDIA GeForce RTX 3090 Ti 992,1 tok/sAMD Radeon AI PRO R9700 667,0 tok/sNVIDIA GB10 (DGX Spark) 367,8 tok/sNVIDIA GeForce RTX 2060 125,7 tok/s

CPUby processor

AMD Ryzen 9 9950X 16-Core Processor 2.182,7 tok/sAMD Ryzen Threadripper PRO 9965WX 24-Cores 1.937,7 tok/sAMD Ryzen 7 5800X3D 8-Core Processor 1.878,7 tok/s★ AMD Ryzen Threadripper PRO 7955WX 16-Cores 1.485,1 tok/s this runAMD Ryzen Threadripper PRO 5975WX 32-Cores 1.197,0 tok/sAMD Ryzen 9 8945HX with Radeon Graphics 992,1 tok/sNVIDIA Grace 367,8 tok/sIntel(R) Core(TM) i5-7400 CPU @ 3.00GHz 125,7 tok/sIntel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz 8,0 tok/s

MBby mainboard

ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 2.182,7 tok/s★ ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 1.937,7 tok/s this runASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING 1.878,7 tok/sASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 1.197,0 tok/sMeigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) 992,1 tok/sASUSTeK COMPUTER INC. GX10 367,8 tok/sASRock H110 Pro BTC+ 125,7 tok/sDell Inc. PowerEdge R820 8,0 tok/s

ENGby engine

llama.cpp 2.182,7 tok/s★ vLLM 1.485,1 tok/s this run

DRVby driver

unbekannt 2.182,7 tok/sNVIDIA 590.48.01 / CUDA 13.1 367,8 tok/s

💰 Economics

Economics of this run

Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (5× concurrent). Methodology →

⚙️ ConfigurationAll metrics and charts below follow these settings – based on a 24-month runtime.Save to URL Reset

⚡ Electricity price EUR/kWh

⚙️ System utilization 100 %

🖥️ Acquisition EUR

🔌 Idle 95 W

⚡ TDP 671 W

☁️ External LLM (API) show

Input €/1M Output €/1M Input per output token

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 0.062

Token / kWh4.83M

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)56.73B

☁️ 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

	Nemotron-3-Nano-4B2x NVIDIA RTX A6000	Nemotron-3-Nano-4BNVIDIA RTX PRO 6000 Blackwell Workstation Edition	Nemotron-3-Nano-4BNVIDIA GeForce RTX 5090	Nemotron-3-Nano-4B3x 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)	–	–	–	–

2× NVIDIA RTX A6000 · this run 899 tok/s NVIDIA RTX PRO 6000 Blackwell Workstation Edition 1,189 tok/s NVIDIA GeForce RTX 5090 1,165 tok/s 3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 1,091 tok/s

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.