Card × model benchmark

Meta Llama 3.1 8B Instruct on RTX 5080 Q4_K_M

Smooth

On an RTX 5080 (16 GB), Meta Llama 3.1 8B Instruct in Q4_K_M generates 124 tokens/s and reads the prompt at 5 100 tokens/s, using 6,0 Go of video memory.

Median of 1 run · latest on 04/08/26

Demo data: this combination has not actually been measured yet.

124 tok/s

Generation

5 100 tok/s

Prompt processing

6,0 Go

VRAM used (peak)

250 W

Average power

0,50 tok/s/W

Efficiency

0,14 €/M tok

Electricity / M tokens · 0,25 €/kWh

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RTX 5080 page All cards on Meta Llama 3.1 8B Instruct Feel the speed Rent in the cloud

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What about a longer context?

An estimate, not a measurement: the KV cache grows with context, takes VRAM and slows generation down.

Context	KV cache	Estimated VRAM	Fits in 16 GB?	Estimated speed
4 096	0,5 Go	6,5 Go	yes	≈ 114 tok/s
8 192	1,0 Go	7,0 Go	yes	≈ 104 tok/s
16 384	2,0 Go	8,0 Go	yes	≈ 89,2 tok/s
32 768	4,0 Go	10,0 Go	yes	≈ 69,0 tok/s
65 536	8,0 Go	14,0 Go	yes	≈ 47,5 tok/s
131 072	16,0 Go	22,0 Go	no	—

KV cache per token = 2 × 32 layers × 8 KV heads × 128 × 2 bytes (f16). Estimated VRAM = measured VRAM + added KV cache. Speed ≈ measured speed × weights ÷ (weights + added KV cache) — attention compute is not modelled, the real drop is slightly larger. Fine-tune it in the “Configurator”

Meta Llama 3.1 8B Instruct on other cards

Card	VRAM	Generation	Difference	Price
RTX 5070 Ti	16 Go	151 tok/s	+21,8 %	1 400 €
RTX 4090demo	24 Go	132 tok/s	+6,5 %	—
RTX 5080demo	16 Go	124 tok/s	this card	1 850 €
RTX 4080demo	16 Go	103 tok/s	−16,9 %	780 €
RTX 4070 Ti	12 Go	89,6 tok/s	−27,7 %	927 €
RTX 4070	12 Go	82,3 tok/s	−33,7 %	595 €
RTX 3060demo	12 Go	48,0 tok/s	−61,3 %	260 €

All measurements

Date	Source	Type	Generation	Prompt	VRAM	Max temp.	Power	llama.cpp
04/08/26	demo	standard	124	5 100	6,0 Go	64 °C	250 W	—

Protocol: llama-bench (llama.cpp), prompt 512 + generation 128 tokens, model fully loaded in VRAM. VRAM used = system peak (includes the OS, ~0.5 to 1 GB more than the model alone). Measure my card