Card × model benchmark
Gemma 3n E4B on RTX 4070 Ti Q4_K_M
SmoothOn an RTX 4070 Ti (12 GB), Gemma 3n E4B in Q4_K_M generates 107 tokens/s and reads the prompt at 5 280 tokens/s, using 4,0 Go of video memory.
Median of 1 run · latest on 25/09/26
107 tok/s
Generation
5 280 tok/s
Prompt processing
4,0 Go
VRAM used (peak)
126 W
Average power
0,85 tok/s/W
Efficiency
0,08 €/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 | 0,1 Go | 4,0 Go | yes | ≈ 106 tok/s |
| 8 192 | 0,1 Go | 4,1 Go | yes | ≈ 105 tok/s |
| 16 384 | 0,2 Go | 4,2 Go | yes | ≈ 102 tok/s |
| 32 768 | 0,4 Go | 4,4 Go | yes | ≈ 97,6 tok/s |
KV cache per token = 2 × 7 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 | 96,3 | 4 582 | 4,3 Go | 66 °C | 183 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | context 16 384ASUS ROG Strix | 101 | 4 912 | 4,2 Go | 64 °C | 167 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | context 8 192ASUS ROG Strix | 104 | 5 011 | 4,1 Go | 64 °C | 154 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | standardASUS ROG Strix | 107 | 5 280 | 4,0 Go | 61 °C | 126 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