Card × model benchmark

Ministral 3 8B on RTX 4070 Ti Q4_K_M

Smooth

On an RTX 4070 Ti (12 GB), Ministral 3 8B in Q4_K_M generates 84,0 tokens/s and reads the prompt at 5 555 tokens/s, using 5,6 Go of video memory.

Median of 1 run · latest on 25/09/26

84,0 tok/s

Generation

5 555 tok/s

Prompt processing

5,6 Go

VRAM used (peak)

149 W

Average power

0,56 tok/s/W

Efficiency

0,12 €/M tok

Electricity / M tokens · 0,25 €/kWh

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RTX 4070 Ti page All cards on Ministral 3 8B 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 12 GB?	Estimated speed
4 096	0,5 Go	6,0 Go	yes	≈ 77,3 tok/s
8 192	1,1 Go	6,5 Go	yes	≈ 70,7 tok/s
16 384	2,1 Go	7,6 Go	yes	≈ 60,3 tok/s
32 768	4,3 Go	9,7 Go	yes	≈ 46,6 tok/s
65 536	8,5 Go	14,0 Go	no	—
131 072	17,0 Go	22,5 Go	no	—

KV cache per token = 2 × 34 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”

Other models measured on the RTX 4070 Ti

Gemma 3 270M Q4_K_M 728 tok/s LFM2.5 1.2B Q4_K_M 473 tok/s Llama 3.2 1B Q4_K_M 442 tok/s R1 Distill 1.5B Qwen Q4_K_M 328 tok/s Gemma 2 2B Q4_K_M 202 tok/s Llama 3.2 3B Instruct Q4_K_M 189 tok/s Ministral 3 3B Q4_K_M 173 tok/s Granite 4.1 3B Q4_K_M 166 tok/s Phi-4 mini 3.8B Q4_K_M 159 tok/s Gemma 3n E2B Q4_K_M 163 tok/s Gemma 4 E2B Q4_K_M 198 tok/s Gemma 3n E4B Q4_K_M 107 tok/s Mistral 7B 7B Q4_K_M 98,1 tok/s Qwen2.5 7B Instruct Q4_K_M 98,8 tok/s R1 Distill 7B Qwen Q4_K_M 97,6 tok/s Qwen2.5 Coder 7B Q4_K_M 96,7 tok/s Meta Llama 3.1 8B Instruct Q4_K_M 91,9 tok/s R1 0528 (Qwen3) 8B Q4_K_M 90,1 tok/s Gemma 4 E4B Q4_K_M 114 tok/s Gemma 2 9B Q4_K_M 72,1 tok/s Gemma 4 12B Q4_K_M 53,8 tok/s Ministral 3 14B Q4_K_M 53,8 tok/s Qwen2.5 14B Instruct Q4_K_M 50,5 tok/s DeepSeek R1 Distill Qwen 14B Q4_K_M 51,1 tok/s Qwen2.5 Coder 14B Q4_K_M 50,3 tok/s Phi-4 Q4_K_M 50,8 tok/s Coder V2 Lite 16B-A2.4B Q4_K_M 189 tok/s

All measurements

Date	Source	Type	Generation	Prompt	VRAM	Max temp.	Power	llama.cpp
25/09/26	SephiGame	context 32 768ASUS ROG Strix	45,1	1 240	9,8 Go	68 °C	202 W	llama.cpp 96278e39f
25/09/26	SephiGame	context 16 384ASUS ROG Strix	59,1	2 326	7,7 Go	68 °C	182 W	llama.cpp 96278e39f
25/09/26	SephiGame	context 8 192ASUS ROG Strix	69,1	4 312	6,6 Go	67 °C	174 W	llama.cpp 96278e39f
25/09/26	SephiGame	standardASUS ROG Strix	84,0	5 555	5,6 Go	59 °C	149 W	llama.cpp 96278e39f

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