# LLM-Benchmark Konfiguration # Modell : Mistral-Small-3.1-24B-Instruct-2503 # Engine : vLLM # Run-ID : run-20260902-060236-74d4bf # 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
execution_type	local

All benchmarks of this model To leaderboard

Model comparison

Mistral-Small-3.1-24B-Instruct-2503 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 A6000 214,9 tok/sAMD Radeon RX 7900 XTX 170,1 tok/sAMD Radeon PRO W7900 Dual Slot 150,4 tok/s★ AMD Radeon PRO W7800 48GB 141,9 tok/s this runAMD Radeon AI PRO R9700 133,1 tok/sNVIDIA RTX PRO 6000 Blackwell Workstation Edition 88,3 tok/sAMD Radeon 8060S Graphics 31,3 tok/sNVIDIA Tesla P100 PCIe 16GB 23,8 tok/s

CPUby processor

AMD Ryzen Threadripper PRO 7955WX 16-Cores 214,9 tok/sIntel(R) Xeon(R) CPU E5-4657L v2 @ 2.40GHz 170,1 tok/sAMD Ryzen Threadripper PRO 3955WX 16-Cores 151,5 tok/s★ AMD Ryzen Threadripper PRO 5975WX 32-Cores 150,4 tok/s this runAMD Ryzen 3 3100 4-Core Processor 133,1 tok/sAMD Ryzen 9 9950X 16-Core Processor 88,3 tok/sAMD RYZEN AI MAX+ 395 w/ Radeon 8060S 31,3 tok/sAMD Ryzen 9 7945HX with Radeon Graphics 23,8 tok/s

MBby mainboard

ASUSTeK COMPUTER INC. Pro WS WRX90E-SAGE SE 214,9 tok/sDell Inc. PowerEdge R820 170,1 tok/s★ ASUSTeK COMPUTER INC. Pro WS WRX80E-SAGE SE WIFI 151,5 tok/s this runASUSTeK COMPUTER INC. ROG STRIX X570-F GAMING 133,1 tok/sASUSTeK COMPUTER INC. ProArt X870E-CREATOR WIFI 88,3 tok/sMeigao Innovation Technology (Shen Zhen) Co., Ltd SHWSA (MS-S1 MAX) 31,3 tok/sShenzhen Meigao Electronic Equipment Co.,Ltd F1FXM (DeskMini Series) 23,8 tok/s

ENGby engine

llama.cpp 214,9 tok/s★ vLLM 99,3 tok/s this rununbekannt 33,1 tok/s

DRVby driver

unbekannt 214,9 tok/sAMD 7.0.0-27-generic 33,1 tok/s

💰 Economics

Economics of this run

Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (10× 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 10 W

⚡ TDP 530 W

☁️ External LLM (API) show

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

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 0.49

Token / kWh606.57K

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)5.63B

☁️ 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

	Mistral-Small-3.1-24B-Instruct-25032x AMD Radeon PRO W7800 48GB	Mistral-Small-3.1-24B-Instruct-25032x NVIDIA RTX A6000	Mistral-Small-3.1-24B-Instruct-25032x NVIDIA RTX A6000	Mistral-Small-3.1-24B-Instruct-25032x NVIDIA RTX A6000
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× AMD Radeon PRO W7800 48GB · this run 89 tok/s 2× NVIDIA RTX A6000 215 tok/s 2× NVIDIA RTX A6000 212 tok/s 2× NVIDIA RTX A6000 211 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.