Contributed byMario AlkaMeta Meta-Llama-3.1-8B-Instruct
Performance benchmark · measured on 06.08.2026 16:42
run-20260807-053422-88d2bbPerformance benchmark · Primary metric: Generation-Speed (tok/s) · 1× concurrent
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: Intel Arc Pro B70 · 32 GB VRAM
CPU: AMD Ryzen 9 7945HX with Radeon Graphics
RAM: 29 GB
Mainboard: Shenzhen Meigao Electronic Equipment Co.,Ltd DRFXI (MotherBoard Series)
Setup
Runtime: openclaw_cli
Quantization: -
Driver: Intel 26.18.38308.4
Model: Meta-Llama-3.1-8B-Instruct
Anmerkung
Arc B70 SYCL post-reboot GPU 2026-08-06
Meta-Llama-3.1-8B-Instruct 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
CPUby processor
MBby mainboard
DRVby driver
Economics of this run
Operating cost, TCO and comparison with the next-best runs of the same model at identical concurrency (1× concurrent). Methodology →
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 (0 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
| Meta-Llama-3.1-8B-InstructIntel Arc Pro B70 | Meta-Llama-3.1-8B-InstructNVIDIA GeForce RTX 5090 | Meta-Llama-3.1-8B-InstructNVIDIA RTX PRO 6000 Blackwell Workstation Edition | Meta-Llama-3.1-8B-Instruct3x 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.
Mario Alka Administrator
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.