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Contributed byMario AlkaNVIDIA

Nemotron-3-Nano-30B-A3B

Performance benchmark · measured on 16.09.2026 19:13

Benchmark-IDrun-20260916-172330-9978e2
Timebench 3 - Kombi (Prefill + Generation)MoE30BRuntime: llama.cppQuantisierung: Q4_K_M
Generation13,88tok/s
Prefill24,13tok/s
Time to First Token89.271,50ms
Total duration273,72s
Concurrency1parallel
Ranking in the field
1241of 1571 systems

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

This run is better than 21 % of all comparable systems.
Generation 13,9 tok/s
-82 % vs Ø 78,5
Prefill 24,1 tok/s
-99 % vs Ø 2.815,1
Time to First Token 89.272 ms
+227 % vs Ø 27.324
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 NVIDIA GeForce RTX 2060 · 6 GB VRAM
CPU: 4x Intel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz
RAM: 504 GB
Mainboard: Dell Inc. PowerEdge R820

Setup

Runtime: llama.cpp
Quantization: Q4_K_M
Model: Nemotron-3-Nano-30B-A3B

Configuration

benchmark-konfiguration — run-20260916-172330-9978e2
# LLM-Benchmark Konfiguration # Modell : Nemotron-3-Nano-30B-A3B # Engine : llama.cpp # Run-ID : run-20260916-172330-9978e2 # GPU : 2x NVIDIA GeForce RTX 2060 # CPU : 4x Intel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz # RAM : 504 GB bench@llm-benchmark:~$ llama-server \ -m nvidia_Nemotron-3-Nano-30B-A3B-Q4_K_M.gguf Q4_K_M RAM-Offload '(moe,' ngl=0, 503GB DDR3, 2x RTX '2060)'
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
Modellpfad?Pfad zur GGUF-Modelldatei, die geladen und ausgeliefert wird.nvidia_Nemotron-3-Nano-30B-A3B-Q4_K_M.gguf

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Model comparison

Nemotron-3-Nano-30B-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

2.3031.7271.1515760,003.8627.72411.586Prefill (tok/s)Generation (tok/s)NVIDIA RTX PRO 6000 Blackwell Workstation Edition - 1.773,5 tok/s Generation, 9.352 tok/s Prefill, TTFT 2.935 ms (6 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 5090 - 1.722,1 tok/s Generation, 5.965 tok/s Prefill, TTFT 3.591 ms (3 Laufe)NVIDIA GeForce RTX 50...NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition - 1.654,6 tok/s Generation, 8.091 tok/s Prefill, TTFT 3.398 ms (9 Laufe)NVIDIA RTX PRO 6000 B...NVIDIA GeForce RTX 3090 Ti - 897,5 tok/s Generation, 3.945 tok/s Prefill, TTFT 4.691 ms (6 Laufe)NVIDIA GeForce RTX 30...NVIDIA RTX A6000 - 756,7 tok/s Generation, 7.661 tok/s Prefill, TTFT 3.400 ms (24 Laufe)NVIDIA RTX A6000NVIDIA GeForce RTX 5070 Ti - 263,3 tok/s Generation, 688 tok/s Prefill, TTFT 27.273 ms (3 Laufe)NVIDIA GeForce RTX 50...AMD Radeon AI PRO R9700 - 217,4 tok/s Generation, 3.127 tok/s Prefill, TTFT 25.253 ms (28 Laufe)AMD Radeon AI PRO R97...NVIDIA GB10 (DGX Spark) - 58,3 tok/s Generation, 5.466 tok/s Prefill, TTFT 395 ms (1 Lauf)NVIDIA GB10 (DGX Spar...NVIDIA GeForce RTX 2060 - 15,1 tok/s Generation, 54 tok/s Prefill, TTFT 172.440 ms (5 Laufe) | DIESER LAUF★ NVIDIA GeForce RTX 20...
NVIDIA RTX PRO 6000 Blackwell Workstation Edition 1.773,5 tok/sNVIDIA GeForce RTX 5090 1.722,1 tok/sNVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 1.654,6 tok/sNVIDIA GeForce RTX 3090 Ti 897,5 tok/sNVIDIA RTX A6000 756,7 tok/sNVIDIA GeForce RTX 5070 Ti 263,3 tok/sAMD Radeon AI PRO R9700 217,4 tok/sNVIDIA GB10 (DGX Spark) 58,3 tok/s★ NVIDIA GeForce RTX 2060 15,1 tok/s this run

CPUby processor

2.3041.7281.1525760,003.8647.72711.591Prefill (tok/s)Generation (tok/s)AMD Ryzen 9 9950X 16-Core Processor - 1.773,5 tok/s Generation, 9.352 tok/s Prefill, TTFT 2.935 ms (6 Laufe)AMD Ryzen 9 9950X 16-...AMD Ryzen 7 5800X3D 8-Core Processor - 1.722,1 tok/s Generation, 5.965 tok/s Prefill, TTFT 3.591 ms (3 Laufe)AMD Ryzen 7 5800X3D 8...AMD Ryzen Threadripper PRO 9965WX 24-Cores - 1.654,6 tok/s Generation, 8.091 tok/s Prefill, TTFT 3.398 ms (9 Laufe)AMD Ryzen Threadrippe...AMD Ryzen 9 8945HX with Radeon Graphics - 897,5 tok/s Generation, 3.908 tok/s Prefill, TTFT 6.463 ms (3 Laufe)AMD Ryzen 9 8945HX wi...AMD Ryzen Threadripper PRO 7955WX 16-Cores - 756,7 tok/s Generation, 5.219 tok/s Prefill, TTFT 15.167 ms (52 Laufe)AMD Ryzen Threadrippe...AMD Ryzen 5 5600X 6-Core Processor - 404,7 tok/s Generation, 3.981 tok/s Prefill, TTFT 2.919 ms (3 Laufe)AMD Ryzen 5 5600X 6-C...AMD Ryzen Threadripper PRO 5975WX 32-Cores - 263,3 tok/s Generation, 688 tok/s Prefill, TTFT 27.273 ms (3 Laufe)AMD Ryzen Threadrippe...NVIDIA Grace - 58,3 tok/s Generation, 5.466 tok/s Prefill, TTFT 395 ms (1 Lauf)NVIDIA GraceIntel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz - 6,6 tok/s Generation, 72 tok/s Prefill, TTFT 131.051 ms (3 Laufe)Intel(R) Xeon(R) CPU ...Intel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz - 15,1 tok/s Generation, 26 tok/s Prefill, TTFT 234.523 ms (2 Laufe) | DIESER LAUF★ Intel(R) Xeon(R) CPU ...
AMD Ryzen 9 9950X 16-Core Processor 1.773,5 tok/sAMD Ryzen 7 5800X3D 8-Core Processor 1.722,1 tok/sAMD Ryzen Threadripper PRO 9965WX 24-Cores 1.654,6 tok/sAMD Ryzen 9 8945HX with Radeon Graphics 897,5 tok/sAMD Ryzen Threadripper PRO 7955WX 16-Cores 756,7 tok/sAMD Ryzen 5 5600X 6-Core Processor 404,7 tok/sAMD Ryzen Threadripper PRO 5975WX 32-Cores 263,3 tok/sNVIDIA Grace 58,3 tok/s★ Intel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz 15,1 tok/s this runIntel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz 6,6 tok/s

MBby mainboard

2.3031.7271.1515760,003.8627.72411.586Prefill (tok/s)Generation (tok/s)ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI - 1.773,5 tok/s Generation, 9.352 tok/s Prefill, TTFT 2.935 ms (6 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING - 1.722,1 tok/s Generation, 5.965 tok/s Prefill, TTFT 3.591 ms (3 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE - 1.654,6 tok/s Generation, 5.643 tok/s Prefill, TTFT 13.430 ms (61 Laufe)ASUSTeK COMPUTER INC....Meigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) - 897,5 tok/s Generation, 3.908 tok/s Prefill, TTFT 6.463 ms (3 Laufe)Meigao Innovation Tec...ASUSTeK COMPUTER INC. PRIME A520M-K - 404,7 tok/s Generation, 3.981 tok/s Prefill, TTFT 2.919 ms (3 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI - 263,3 tok/s Generation, 688 tok/s Prefill, TTFT 27.273 ms (3 Laufe)ASUSTeK COMPUTER INC....ASUSTeK COMPUTER INC. GX10 - 58,3 tok/s Generation, 5.466 tok/s Prefill, TTFT 395 ms (1 Lauf)ASUSTeK COMPUTER INC....Dell Inc. PowerEdge R820 - 15,1 tok/s Generation, 54 tok/s Prefill, TTFT 172.440 ms (5 Laufe) | DIESER LAUF★ Dell Inc. PowerEdge R...
ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 1.773,5 tok/sASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING 1.722,1 tok/sASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 1.654,6 tok/sMeigao Innovation Technology (Shen Zhen) Co., Ltd DRFXL (MotherBoard Series) 897,5 tok/sASUSTeK COMPUTER INC. PRIME A520M-K 404,7 tok/sASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 263,3 tok/sASUSTeK COMPUTER INC. GX10 58,3 tok/s★ Dell Inc. PowerEdge R820 15,1 tok/s this run

ENGby engine

2.2251.6681.1125560,01.7026.05610.41014.764Prefill (tok/s)Generation (tok/s)vLLM - 588,5 tok/s Generation, 12.484 tok/s Prefill, TTFT 1.330 ms (13 Laufe)vLLMunbekannt - 404,7 tok/s Generation, 3.981 tok/s Prefill, TTFT 2.919 ms (3 Laufe)unbekanntllama.cpp - 1.773,5 tok/s Generation, 3.992 tok/s Prefill, TTFT 26.002 ms (69 Laufe) | DIESER LAUF★ llama.cpp
★ llama.cpp 1.773,5 tok/s this runvLLM 588,5 tok/sunbekannt 404,7 tok/s

DRVby driver

2.2941.7201.1475730,04.9295.2285.5275.826Prefill (tok/s)Generation (tok/s)unbekannt - 1.773,5 tok/s Generation, 5.288 tok/s Prefill, TTFT 21.664 ms (84 Laufe)unbekanntNVIDIA 590.48.01 / CUDA 13.1 - 58,3 tok/s Generation, 5.466 tok/s Prefill, TTFT 395 ms (1 Lauf)NVIDIA 590.48.01 / CU...
unbekannt 1.773,5 tok/sNVIDIA 590.48.01 / CUDA 13.1 58,3 tok/s
💰 Economics

Economics of this run

Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (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 55 W
⚡ TDP 359 W
☁️ External LLM (API)
Electricity0.30 EUR/kWh
Avg power (incl. idle)359 W estimated (TDP)GPU 320 + CPU 29 + Board 10 W full load
Avg cost / hourEUR 0.11
Electricity / 1M tokensEUR 2.15
Token / kWh139.28K
Acquisition (system)EUR 2,445 partial priceGPU EUR 220 · CPU EUR 59 · RAM EUR 2,016 · PSU EUR 150
Electricity (2 years)
TCO (2 years)EUR 4,331
Output tokens (2 years)875.44M
☁️ 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 (55 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-30B-A3B2x NVIDIA GeForce RTX 2060Nemotron-3-Nano-30B-A3BNVIDIA GeForce RTX 5090Nemotron-3-Nano-30B-A3BNVIDIA RTX PRO 6000 Blackwell Workstation EditionNemotron-3-Nano-30B-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.