TensorFold engine 1.2.0 is out 🙌 Qwen3.8-27B with MLX 4-bit weights and DFlash2, compared with 1.1.9: • M3 Ultra: 14.4% faster decoding with one stream, 44.2% higher combined throughput with 16. • M5 Ultra: 5.8% faster decoding with one stream, 25.2% higher combined throughput with 16. New support includes: • MiniMax-M3.1-Flash on Metal. • NVFP4 Qwen3.6-35B-A3B and dense EXL3 Qwen3.8-27B on CUDA. • Gemma 4 E4B on Intel Arc Pro B70. The measured speedups kept matching tokens. Qwen-VL image replies can differ from 1.1.9 because image preparation now matches the checkpoint's own processor. Huge thanks to everyone credited in this release: @bhcc2025 @Bizuayeu @diwakergupta @jvr0x @jayleaton @joshuaswarren @woolsey @petruspennanen @volatilemarkts @MiaAI_lab @plotarmordev And on GitHub: AbrahamCete, akol1, alexderz, Arminova, BadAd84, BlivionIaG, BobClawblaw, fche, gilby, jrb-ai, jschmied, laudney, Mirrdhyn, mrv777, ppardus, simon-lin88, ThomasHalwax, valacroix and wojo. Thank you for the PRs, reviews, testing, bug reports and hardware access. The time and knowledge you keep sharing with TensorFold mean a lot to me. Apologies if I've missed anyone.