Card × model benchmark
Qwen2.5 Coder 0.5B on RTX 5070 Ti Q4_K_M
SmoothOn an RTX 5070 Ti (16 GB), Qwen2.5 Coder 0.5B in Q4_K_M generates 805 tokens/s and reads the prompt at 55 586 tokens/s, using 1,7 Go of video memory.
Median of 1 run · latest on 25/09/26
805 tok/s
Generation
55 586 tok/s
Prompt processing
1,7 Go
VRAM used (peak)
42 W
Average power
19,17 tok/s/W
Efficiency
0,00 €/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 16 GB? | Estimated speed |
|---|---|---|---|---|
| 4 096 | 0,0 Go | 1,8 Go | yes | ≈ 733 tok/s |
| 8 192 | 0,1 Go | 1,8 Go | yes | ≈ 662 tok/s |
| 16 384 | 0,2 Go | 1,9 Go | yes | ≈ 555 tok/s |
| 32 768 | 0,4 Go | 2,1 Go | yes | ≈ 419 tok/s |
KV cache per token = 2 × 24 layers × 2 KV heads × 64 × 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 5070 Ti
All measurements
| Date | Source | Type | Generation | Prompt | VRAM | Max temp. | Power | llama.cpp |
|---|---|---|---|---|---|---|---|---|
| 25/09/26 | French_Girl_13 | context 32 768MSI Gaming X Trio | 537 | 19 406 | 2,3 Go | 54 °C | 112 W | llama.cpp 96278e39f |
| 25/09/26 | French_Girl_13 | context 16 384MSI Gaming X Trio | 621 | 28 021 | 2,2 Go | 53 °C | 87 W | llama.cpp 96278e39f |
| 25/09/26 | French_Girl_13 | context 8 192MSI Gaming X Trio | 675 | 36 504 | 2,0 Go | 47 °C | 45 W | llama.cpp 96278e39f |
| 25/09/26 | French_Girl_13 | standardMSI Gaming X Trio | 805 | 55 586 | 1,7 Go | 48 °C | 42 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