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SenseTime published a detailed technical report (arXiv

2026-06-07 · 10:46 UTC ·@heyshrutimishra ·0 min read

Brief

SenseTime’s OpenSenseNova release (arXiv:2605.12500) open-sources the 38B-A3B MoE model SenseNova-U1-A3B-MoT and provides an 8-step distilled LoRA that shrinks sampling from 100 to 8 steps and drops H100 inference from ~23s to ~2s. The package includes ComfyUI-compatible workflows for text-to-image, editing, and interleaved generation, plus GitHub, Discord, and Hugging Face resources for builders.

Why it matters

SenseTime published a detailed technical report (arXiv:2605.12500) and open-sourced weights for SenseNova-U1-A3B-MoT, a 38B A3B mixture-of-experts (MoE) model.

Key details

  • An 8-step distilled LoRA reduces generation from 100 steps to 8 and cuts H100 inference latency from ~23s to ~2s, with ready-to-run ComfyUI workflows for text-to-image, editing, and interleaved generation.
  • Official resources include GitHub (github.com/OpenSenseNova/Sen…), a Discord (discord.gg/BuTXPHmQub), and a Hugging Face collection (huggingface.co/collections/s…) for developers using open models.
Source evidence

4/ Everything is open. Here is where to start.

The full technical report is out, the most detailed disclosure yet from @SenseTime_AI: arxiv.org/abs/2605.12500

The weights are open-sourced too: SenseNova-U1-A3B-MoT, a 38B-A3B MoE.

ComfyUI is supported now. A new 8-step distilled LoRA takes generation from 100 steps to 8 and cuts H100 inference from 23s to 2s, with ready-to-run workflows for text-to-image, editing, and interleaved generation.

GitHub: github.com/OpenSenseNova/Sen…
Discord: discord.gg/BuTXPHmQub
Hugging Face: huggingface.co/collections/s…

If you build with open models, you must check it out