Card × model benchmark
Gemma 3n E2B on RTX 4070 Ti Q4_K_M
SmoothOn an RTX 4070 Ti (12 GB), Gemma 3n E2B in Q4_K_M generates 163 tokens/s and reads the prompt at 8 222 tokens/s, using 2,5 Go of video memory.
Median of 1 run · latest on 25/09/26
163 tok/s
Generation
8 222 tok/s
Prompt processing
2,5 Go
VRAM used (peak)
106 W
Average power
1,53 tok/s/W
Efficiency
0,05 €/M tok
Electricity / M tokens · 0,25 €/kWh
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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 | 0,0 Go | 2,5 Go | yes | ≈ 160 tok/s |
| 8 192 | 0,1 Go | 2,5 Go | yes | ≈ 158 tok/s |
| 16 384 | 0,2 Go | 2,6 Go | yes | ≈ 153 tok/s |
| 32 768 | 0,4 Go | 2,8 Go | yes | ≈ 144 tok/s |
KV cache per token = 2 × 6 layers × 2 KV heads × 256 × 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
All measurements
| Date | Source | Type | Generation | Prompt | VRAM | Max temp. | Power | llama.cpp |
|---|---|---|---|---|---|---|---|---|
| 25/09/26 | SephiGame | context 32 768ASUS ROG Strix | 139 | 6 830 | 3,1 Go | 65 °C | 166 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | context 16 384ASUS ROG Strix | 150 | 7 306 | 3,0 Go | 63 °C | 144 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | context 8 192ASUS ROG Strix | 154 | 7 702 | 2,9 Go | 62 °C | 134 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | standardASUS ROG Strix | 163 | 8 222 | 2,5 Go | 57 °C | 106 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