Lance AI By bytedance: Modern Open Source Unified Multimodal

What is Lance AI by ByteDance: Modern Open Source Unified Multimodal

Lance AI is a small but strong 3B model from ByteDance that works with both images and videos. It can understand, create, and edit content with text prompts and examples. It was trained with a careful multi task plan using no more than 128 GPUs.

Lance brings many skills into one place. You can ask it to write a caption, answer questions about a chart, make a new image from text, edit a picture, turn text into video, and even make smart plans in video scenes.

Overview

Here is a quick look at the project in one place.

Type	Open source unified multimodal model
Main purpose	Image and video understanding, generation, and editing
Creator	Intelligent Creation Team, ByteDance
Model size	3B parameters
Training budget	No more than 128 GPUs with a staged multi task recipe
Inputs	Text, images, video
Outputs	Images, videos, captions, answers, edits
Core ideas	Shared sequence for text and pixels, separate experts for understanding and generation
Key methods	ViT tokens, VAE latents, generalized 3D causal attention, MaPE
Demos	Text to video, video editing, video reasoning, text to image, image editing, image understanding
Availability	Paper, code, and models listed on the project site

If you want to compare with a strong text to image system, check our short guide on Hunyuanimage 3.

Key Features

• One model for many jobs. It does image and video tasks in one place.
• Rich generation. Text to video, text to image, and creative edits for pictures and clips.
• Smart understanding. It answers questions, reads charts and text in images, and writes short or long captions.
• Edit with care. It can replace subjects, change styles, add or remove objects, and keep the layout stable.
• Planning in motion. It shows grid navigation and physics aware moves over time.
• Video quality boost. Demos are shown with 2x super resolution and 2x frame interpolation.

Use Cases

• Creative work. Make concept images, mood clips, storyboards, and quick drafts for ads or films.
• Marketing and media. Swap backgrounds, change styles, recolor items, and add or remove objects for fast content refresh.
• Education and reports. Ask questions about charts, read numbers from tables, and turn complex scenes into clear text.
• Product and UX teams. Try edits and motion ideas before full shoots to save time and cost.

Performance & Showcases

Below are short showcases that match the labels from the project page.

Showcase 1 — TEXT-TO-VIDEO This demo shows TEXT-TO-VIDEO results from simple text prompts. It focuses on character motion, two person scenes, and dreamy looks. Quality is displayed with 2x super resolution and 2x frame interpolation.

Showcase 2 — VIDEO EDITING This demo highlights VIDEO EDITING guided by prompts. It covers background change, subject swap, object edits, style transfer, and simple action edits. Results keep the scene layout and apply clean changes.

Showcase 3 — VIDEO REASONING This demo presents VIDEO REASONING with question answering and captioning. It tracks motion and time to form correct answers. It can also write short or longer captions for the same clip.

Showcase 4 — Surfing animal character This clip shows Surfing animal character created from text. It keeps the subject on theme and adds natural water motion. The result is smooth and fun to watch.

Showcase 5 — Robot and dog duet This clip shows Robot and dog duet generated from a prompt. The scene focuses on two subjects and their joint action. Timing across both characters stays in sync.

Showcase 6 — Wizard cat with magic This clip shows Wizard cat with magic based on a text idea. Sparks and motion effects support the theme. The character remains clear and steady across frames.

Benchmarks at a glance

Lance compares well with both unified and task focused models across public tests. It scores an overall 0.90 on GenEVAL for image generation, which tracks object count, color, position, and attributes. On DPG Bench it shows strong relation grounding and solid results across global and entity checks.

How Lance AI by ByteDance Works

Lance keeps one shared sequence for text, images, and video. This lets it learn links between words and pixels in a simple way. After that, it uses different expert parts to do understanding and to do generation.

For understanding, it works on semantic tokens that capture what is in the scene. For generation, it uses clean and noisy latent codes to build and refine images and video. Generalized 3D causal attention helps it handle space and time together.

The Technology Behind It

• Shared interleaved sequence. Text and pixel tokens live together so the model can align them better.
• Separate experts. One expert focuses on meaning and reasoning. The other expert focuses on making pictures and clips.
• Token choices. It uses ViT tokens for meaning and VAE latents for making content.
• Attention for time. Generalized 3D causal attention handles both spatial and temporal context.
• MaPE. This helps reduce interference among different token types and positions.

For a look at tools that mix many skills across inputs, see our note on open multimodal agents.

Examples of What It Can Do

• Text to image: From photoreal to stylized, with solid control over count, color, and layout.
• Image editing: Replace subjects, transfer styles, add or remove items, and keep structure.
• Image understanding: Read charts and documents, answer questions, recognize landmarks and objects.

Getting Started

The project page lists the paper, code, and models. You can explore demos, then visit the code link and the model hub to try it in your own setup. If you plan local tests, check GPU memory and storage first, then follow the official instructions from their repo.

If you are new to running large local models, our quick guide on running Qwen 35B locally can help you plan resources and steps.

Who Is Lance AI For

• Creators who need fast mockups for images and clips.
• Editors who want prompt based edits with source layout kept.
• Researchers and students who study image and video tasks in one model.

FAQ

Is Lance AI open source

Yes. The team lists the paper, code, and model links on the project page. You can review them and test in your own setup.

Can I run Lance AI on my own machine

It is a 3B model, so a modern GPU helps a lot for speed. Start with the official repo notes to see memory needs and supported tools.

What kind of edits can it do on video

It can rewrite backgrounds, add or remove objects, change the subject, restyle looks, and adjust simple actions. Multi turn edits can keep the same subject across steps.

How strong is it on image generation

On GenEVAL, Lance scores 0.90 overall while staying compact at 3B. It tracks color, count, and position well for many prompts.

Does it handle charts and text inside images

Yes. It answers chart questions, reads numbers, and can output captions. The site shows clear examples of this skill.

Image source: Lance AI By bytedance: Modern Open Source Unified Multimodal