SenseTime has introduced SenseNova U1.5, an eight-billion parameter model that unifies understanding, reasoning, and generation within the pixel space into a single native multimodal system.
Unlike existing pipelines that use a vision encoder for perception and a separate variational autoencoder for synthesis, U1.5 maps pixels and text into a common framework without these external modules. This aligns with the company's NEO-unify line, while improving spatial reconstruction to achieve higher accuracy at production resolutions.
The architectural change involves replacing independent MLP patch decoding with a lightweight spatial decoder. Visual tokens are transformed into a two-dimensional feature field and then reconstructed using Pixel Shuffle and local convolutions, allowing neighboring regions to exchange information before pixel finalization.
SenseTime reports that the interface still displays each area as 32x32 per visual token, but it supports native generation up to 4K with fewer seam breaks and textural inconsistencies compared to the previous U1 version. This was made possible by resolution-aware noise conditioning across wider aspect ratios.
The post-training process follows a recipe of specialization followed by unification. Reinforcement learning specialists focus on visual aesthetics, bilingual text rendering, infographic layout, and image editing. Subsequently, multi-expert policy distillation merges these skills into a single student along its own generation trajectories.
SenseTime asserts that U1.5 results surpass U1 in image generation and editing datasets, including competitive bilingual text rendering and multi-reference editing, while maintaining generally high multimodal understanding scores on standard STEM, VQA, and OCR benchmarks.
Alongside the technical report published on arXiv and Hugging Face Papers, SenseTime is making the training code open source, covering controlled fine-tuning, reinforcement learning, and policy distillation. Model assets are available in the SenseNova and Hugging Face collections under the OpenSenseNova organization. This release represents the full U1.5 product, not an early U1.5-Lite-Preview, and is intended for developers who wish to obtain a compact native unified vision model that can be fully explored, customized, and retrained.