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Exact recorded values. Context may be a configured limit; matching filters does not establish identical prompts, offloading or concurrency.
User reports Qwen3.8 Flash-Next at 36.1 t/s on an RTX 4070 Ti Super, up from 30.3 t/s after raising Strata's --adapt-every from 1 to 6. Setup is Strata with UD-Q4_K_XL GGUF on a single card, tested on four Slovak-language chat prompts; the fourth prompt describes 20K tokens of source code. Per-prompt gains ranged from +12% to +55% with UD-Q4_K_XL; a UD-IQ4_XS run reached 63.1 to 71.6 t/s across the same prompts.
NVIDIA RTX 4070 Ti Super · Strata · 10,000 ctx
User reports Qwen3.8 Next at 197 t/s generation and 3,300 t/s prefill on an RTX 4070 Ti Super 16GB. Setup is Strata on CachyOS with Q2 weights, 10k and 20k token prompts, 15.6GB VRAM plus 44GB system RAM used. An IQ3XXS run reached 120 t/s generation and 3,000 t/s prefill with 50GB system RAM used; total system power was 350W.
NVIDIA RTX 4070 Ti Super · Strata · 262,144 ctx
User reports Qwen3.8 Flash-Next at 72 t/s generation and ~1,700 t/s prompt reading on an RTX 4070 Ti Super 16GB. Setup is Strata 0.1.39 with IQ3_S (~84GB) at 256K context, on a Ryzen 9 7950X3D with 128GB DDR5. Out of the box it did 8 t/s; after START-HERE.bat --calibrate it reached 72 t/s. A 17K prompt reads in 8 seconds. User's 27-task coding suite scored 27/27 x3 and HumanEval 159/164. Same model family under llama.cpp with offloading ran at 19 t/s. Keeping the 29GB n-gram table in RAM with --ple-io mmap made results worse (25-26/27 and slower).
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking