Card × model benchmark
Phi-4 on RTX 4070 Ti Q4_K_M
ComfortableOn an RTX 4070 Ti (12 GB), Phi-4 in Q4_K_M generates 50,8 tokens/s and reads the prompt at 3 442 tokens/s, using 9,2 Go of video memory.
Median of 1 run · latest on 25/09/26
50,8 tok/s
Generation
3 442 tok/s
Prompt processing
9,2 Go
VRAM used (peak)
171 W
Average power
0,30 tok/s/W
Efficiency
0,23 €/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 | 0,8 Go | 9,9 Go | yes | ≈ 47,3 tok/s |
| 8 192 | 1,6 Go | 10,6 Go | yes | ≈ 43,8 tok/s |
| 16 384 | 3,1 Go | 12,2 Go | no | — |
KV cache per token = 2 × 40 layers × 10 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”
Phi-4 on other cards
| Card | VRAM | Generation | Difference | Price |
|---|---|---|---|---|
| RTX 5070 Ti | 16 Go | 84,9 tok/s | +67,2 % | — |
| RTX 4070 Ti | 12 Go | 50,8 tok/s | this card | — |
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 16 384ASUS ROG Strix | 4,5 | 92,8 | 11,6 Go | 51 °C | 76 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | context 8 192ASUS ROG Strix | 43,0 | 2 729 | 10,8 Go | 67 °C | 192 W | llama.cpp 96278e39f |
| 25/09/26 | SephiGame | standardASUS ROG Strix | 50,8 | 3 442 | 9,2 Go | 66 °C | 171 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