Open-source codebase for efficient high-resolution image and video generation using linear diffusion transformers, with training and inference pipelines.
OpenSenseNova/SenseNova-U1
Open-source native unified multimodal models from SenseNova that handle image understanding, text-to-image generation, and image editing in one architecture.
Open-source alternative to:Midjourney
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What is it?
SenseNova-U1 and U1.5 are multimodal model series built on the NEO-unify architecture, which removes the separate visual encoder and VAE used by many systems and models language and vision end-to-end. The models cover visual question answering, text-to-image generation, interleaved image-text output, and image editing, with additional checkpoints tuned for infographics and 8-step fast inference.
The repository provides inference scripts for Transformers covering text-to-image, editing, interleaved generation, and visual understanding, along with GGUF quantized inference options and layer-offload VRAM modes for single-GPU setups. Weights are published on Hugging Face and ModelScope, and training code for full-parameter fine-tuning is included.
Key features
- 01Unified model for image understanding, text-to-image generation, and image editing
- 02Native interleaved image-text generation in a single flow
- 03Dedicated infographic model variants with text and layout editing
- 04GGUF quantized checkpoints and layer-offload modes for low-VRAM inference
- 05Full-parameter fine-tuning training code
Use cases
- Generating posters, infographics, or designs with legible Chinese and English text
- Editing existing images with natural-language instructions while preserving unedited regions
- Producing illustrated step-by-step tutorials that mix text and images
- Running multimodal inference on a single consumer GPU using quantized weights
Quick start
- 1
Install the Python dependencies
- 2
Run the text-to-image example with the Transformers quick start
python examples/t2i/inference.py --model_path sensenova/SenseNova-U1.5-8B-MoT --prompt "A formal portrait depicts a man in 18th-century attire seated with a scroll, wearing a red cloak and ornate medals, against a classical landscape with ancient ruins and inscriptions." --output output.png
Things to know
- The model is large (8B parameters), so running it locally needs a capable GPU or a quantized GGUF checkpoint.
- The README lists known issues such as dense text errors, unstable human details, and over-saturated colors.
Topics
FAQ
- What is SenseNova-U1?
- Open-source native unified multimodal models from SenseNova that handle image understanding, text-to-image generation, and image editing in one architecture. SenseNova-U1 and U1.5 are multimodal model series built on the NEO-unify architecture, which removes the separate visual encoder and VAE used by many systems and models language and vision end-to-end. The models cover visual question answering, text-to-image generation, interleaved image-text output, and image editing, with additional checkpoints tuned for infographics and 8-step fast inference.
- Is SenseNova-U1 free to use? What license does it have?
- SenseNova-U1 is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
- Is SenseNova-U1 still maintained?
- Actively maintained. The last commit to SenseNova-U1 was on Oct 1, 2026.
- What can I use SenseNova-U1 for?
- Generating posters, infographics, or designs with legible Chinese and English text Editing existing images with natural-language instructions while preserving unedited regions Producing illustrated step-by-step tutorials that mix text and images Running multimodal inference on a single consumer GPU using quantized weights
- How do I install SenseNova-U1?
- Install the Python dependencies Run the text-to-image example with the Transformers quick start: python examples/t2i/inference.py --model_path sensenova/SenseNova-U1.5-8B-MoT --prompt "A formal portrait depicts a man in 18th-century attire seated with a scroll, wearing a red cloak and ornate medals, against a classical landscape with ancient ruins and inscriptions." --output output.png
- Where can I get SenseNova-U1?
- The source code and installation instructions are on GitHub: https://github.com/OpenSenseNova/SenseNova-U1
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