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.
tensorfold.dev