Döner Bench DeepSeek-V4-Flash IQ2_XS running on a single RTX 3090

https://preview.redd.it/3zcvpbds14hh1.png?width=1911&format=png&auto=webp&s=a79aafb71eeca97638da93d2591902631e897fd5 I tried a test similar to the recent model-quant comparisons, but this time I focused only on: DeepSeek-V4-Flash-0731-IQ2_XS-Experts-Q8_0 model link bullerwins/DeepSeek-V4-Flash-0731-GGUF · Hugging Face Hardware RTX 3090 24 GB 128 GB DDR4 RAM Windows llama.cpp / llama-server Prompt Write a single HTML file with a full-page canvas and no libraries. Simulate a realistic Döner-style kebab skewer rotating vertically in front of a gas-powered heating element. The resulting render is shown in the attached image. Considering that most of the model is quantized to IQ2_XS, I was impressed that it produced a complete and working result. It is obviously not perfect, and some of the finer details and realism are lost, but the overall scene, animation and requested concept are still present. https://pastebin.com/h1VE5aj0 Command used "D:ppllama-server.exe" ^ -m "E:modelsDeepSeek-V4-Flash-0731-IQ2_XS-Experts-Q8_0DeepSeek-V4-Flash-0731-IQ2_XS-Experts-Q8_0.gguf" ^ --fit on ^ --fit-ctx 32768 ^ --fit-target 1024 ^ --jinja --metrics --perf ^ -np 1 ^ -ub 4096 -b 4096 ^ --no-kv-unified ^ --no-mmap ^ --flash-attn on ^ --cache-type-k q8_0 ^ --cache-type-v q8_0 ^ --temp 1.0 --top_k 40 --top_p 1.0 ^ --min-p 0.00 --repeat-penalty 1.0 --presence-penalty 0.0 ^ --threads 14 submitted by /u/nikhilprasanth [link] [comments]

Source: r/LocalLLaMA | 2026-08-03