llama.cpp on the NVIDIA Tesla P40 24GB
On the NVIDIA Tesla P40 24GB, llama.cpp runs Qwen3.6 35B · 3B active at 3-bit at a median 37.9 tokens per second for generation, from 1 plain run (context not stated).
Speed by model on the NVIDIA Tesla P40 24GB
Plain runs only: one device, one request, no speculative decoding, the whole model in memory. Each row is one model size at one bit class, with the other engines' plain runs of the same model on this card beside it. Context length and build still differ between runs, and each side shows its own.
| Model | llama.cpp | Other engines |
|---|---|---|
| Qwen3.6 35B · 3B active 3-bit | 37.9 t/sone report, context not stated | no other engine reported |
5 llama.cpp reports on the NVIDIA Tesla P40 24GB
Newest first. A run on several cards, with speculative decoding, with part of the model in system RAM or with batched requests says so, since each describes a different setup.
- Kimi K2.5 1000B · 32B active · Q2_K_XL5.8 t/s(8 cards, part in system RAM)
- Qwen3.6 27B · IQ4_XS23.7 t/s(speculative decoding)
- Qwen3.6 35B · 3B active · Q3_K_XL37.9 t/s
- Qwen3.6 35B · 3B active · UD-Q3_K_XL51.6 t/s(speculative decoding)
- Qwen3.8 27B · Q8_046.0 t/s(2 cards, speculative decoding)
Frequently asked
How fast is llama.cpp on the NVIDIA Tesla P40 24GB?
On the NVIDIA Tesla P40 24GB, llama.cpp runs Qwen3.6 35B · 3B active at 3-bit at a median 37.9 tokens per second for generation, from 1 plain run (context not stated).