Thanks for the shout-out, @ashxhart! Seeing my name in the 1.0.3 notes, and Mia's shout-out on top, really keeps the motivation up :D The 1.0.3 release binary has no kernels for the RTX 5090. Building from source with one flag fixes it: -Dsm=120, no patch. Same card, same day, Nemotron 3.5 Lightning, llama.cpp with MTP → TensorFold 1.0.3: Code: 458 → 731 tok/s (1.6×) Prose: 354 → 506 tok/s (1.4×) • TensorFold's drafted output matches plain byte for byte, 10 of 10. llama.cpp with MTP changes tokens. • vs 1.0.2: +8% code, +11% prose. • One RTX 5090, Linux, 450 W. Ash's bench_openai.py, greedy, 256 tokens, median of 3 rounds. • Different quants: MLX 4-bit vs GGUF Q4_K_M, quality not compared. llama.cpp MTP not tuned. Build: zig build -Dsm=120 -Doptimize=fast fatbins install zig build -Dsm=120 -Doptimize=fast native