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Contributed byMario AlkaNVIDIA

Nemotron-3-Nano-30B-A3B

Performance benchmark · measured on 26.08.2026 15:28

Benchmark-IDrun-20260826-134908-471995
Timebench 3 - Kombi (Prefill + Generation)MoE30BRuntime: llama.cppQuantisierung: Q8_0
Generation176,89tok/s
Prefill5.266,81tok/s
Time to First Token2.069,00ms
Total duration62,54s
Concurrency5parallel
Ranking in the field
417of 899 systems

Performance benchmark · Primary metric: Generation-Speed (tok/s) · 5× concurrent

This run is better than 54 % of all comparable systems.
Generation 176,9 tok/s
-34 % vs Ø 268,0
Prefill 5.266,8 tok/s
+33 % vs Ø 3.953,1
Time to First Token 2.069 ms
-95 % vs Ø 39.529
Distribution in the field0 – 1.349 tok/s
Ø 268 Median Dieser Lauf

Wie schlägt sich dieser Benchmark mit anderen Modellen?

gemma-4-E2B-itNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260727-181606-0adf6d
1.349,3 tok/s
gemma-4-E2B-itNVIDIA GeForce RTX 5090 · run-20260728-184455-5b4937
1.301,9 tok/s
gemma-4-E2B-it3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-184456-4111a9
1.195,7 tok/s
Nemotron-3-Nano-4BNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260727-181607-30d864
1.188,7 tok/s
Nemotron-3-Nano-4BNVIDIA GeForce RTX 5090 · run-20260728-194135-5432cd
1.164,8 tok/s
gpt-oss-20bNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260728-140954-9e81f9
1.136,3 tok/s
gpt-oss-20bNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260730-035052-09627f
1.135,0 tok/s
gpt-oss-20bNVIDIA GeForce RTX 5090 · run-20260729-032121-058a31
1.113,5 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-836a91
1.090,6 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260727-181606-8b381e
1.077,4 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-b8a818
1.071,0 tok/s
Nemotron-3-Nano-4B3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260728-194136-038e92
1.051,1 tok/s
gpt-oss-20b3× NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition · run-20260729-032121-ffb18a
1.015,5 tok/s
Nemotron-3-Nano-30B-A3B same modelNVIDIA RTX PRO 6000 Blackwell Workstation Edition · run-20260729-032121-305ad6
1.007,8 tok/s
Nemotron-3-Nano-30B-A3B this runNVIDIA RTX A6000 · run-20260826-134908-471995
176,9 tok/s

How does this benchmark compare on other GPUs?

Same model on different hardware · 5× 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: Q8_0
Model: Nemotron-3-Nano-30B-A3B

Configuration

benchmark-konfiguration — run-20260826-134908-471995
# LLM-Benchmark Konfiguration # Modell : Nemotron-3-Nano-30B-A3B # Engine : llama.cpp # Run-ID : run-20260826-134908-471995 # 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 nvidia_Nemotron-3-Nano-30B-A3B-Q8_0.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.nvidia_Nemotron-3-Nano-30B-A3B-Q8_0.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

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

2.3041.7281.1525760,003.8617.72211.583Prefill (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 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...CPU-only - 6,6 tok/s Generation, 72 tok/s Prefill, TTFT 131.051 ms (3 Laufe)CPU-onlyNVIDIA RTX A6000 - 259,4 tok/s Generation, 5.060 tok/s Prefill, TTFT 2.140 ms (6 Laufe) | DIESER LAUF★ NVIDIA RTX A6000
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 GeForce RTX 5070 Ti 263,3 tok/s★ NVIDIA RTX A6000 259,4 tok/s this runAMD Radeon AI PRO R9700 217,4 tok/sNVIDIA GB10 (DGX Spark) 58,3 tok/sCPU-only 6,6 tok/s

CPUby processor

2.3041.7281.1525760,003.8617.72211.583Prefill (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 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 ...AMD Ryzen Threadripper PRO 7955WX 16-Cores - 259,4 tok/s Generation, 3.468 tok/s Prefill, TTFT 21.174 ms (34 Laufe) | DIESER LAUF★ AMD Ryzen Threadrippe...
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 5 5600X 6-Core Processor 404,7 tok/sAMD Ryzen Threadripper PRO 5975WX 32-Cores 263,3 tok/s★ AMD Ryzen Threadripper PRO 7955WX 16-Cores 259,4 tok/s this runNVIDIA Grace 58,3 tok/sIntel(R) Xeon(R) CPU E5-4620 v2 @ 2.60GHz 6,6 tok/s

MBby mainboard

2.3041.7281.1525760,003.8617.72211.583Prefill (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....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 - 6,6 tok/s Generation, 72 tok/s Prefill, TTFT 131.051 ms (3 Laufe)Dell Inc. PowerEdge R...ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE - 1.654,6 tok/s Generation, 4.436 tok/s Prefill, TTFT 17.453 ms (43 Laufe) | DIESER LAUF★ ASUSTeK COMPUTER INC....
ASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 1.773,5 tok/sASUSTeK COMPUTER INC. ROG STRIX B550-A GAMING 1.722,1 tok/s★ ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 1.654,6 tok/s this runMeigao 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/sDell Inc. PowerEdge R820 6,6 tok/s

ENGby engine

2.2251.6681.1125560,01.6735.5799.48513.391Prefill (tok/s)Generation (tok/s)vLLM - 533,5 tok/s Generation, 11.340 tok/s Prefill, TTFT 1.686 ms (7 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, 3.724 tok/s Prefill, TTFT 22.942 ms (55 Laufe) | DIESER LAUF★ llama.cpp
★ llama.cpp 1.773,5 tok/s this runvLLM 533,5 tok/sunbekannt 404,7 tok/s

DRVby driver

2.2941.7201.1475730,04.0484.6855.3235.960Prefill (tok/s)Generation (tok/s)unbekannt - 1.773,5 tok/s Generation, 4.542 tok/s Prefill, TTFT 20.031 ms (64 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 (5× 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 0.033
Token / kWh8.97M
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)11.16B
☁️ 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

Nemotron-3-Nano-30B-A3BNVIDIA RTX A6000Nemotron-3-Nano-30B-A3BNVIDIA RTX PRO 6000 Blackwell Workstation EditionNemotron-3-Nano-30B-A3BNVIDIA GeForce RTX 5090Nemotron-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.