ByteDance is reorganizing its artificial intelligence division to build what could become the world's largest AI model, with over 5 trillion parameters. The Chinese tech giant is dismantling internal silos and creating four specialized departments to streamline development of this massive system, which would dwarf existing competitors' models by a significant margin.

What Is ByteDance Building, and How Big Is It?

ByteDance's new model would contain more than 5 trillion parameters, which are the numerical building blocks that allow AI systems to understand and generate language, images, and video. To put this in perspective, Alibaba's Qwen 3.8-Max contains 2.4 trillion parameters, while Moonshot's K3 has around 2.8 trillion. ByteDance's planned system would be nearly double the size of these already-massive models, making it potentially the largest AI model developed in China to date.

The project is being led by Xiang Liang, head of ByteDance's Seed Foundation, in collaboration with Shen Ke, who oversees pre-training data for large language models. However, the plan remains in its early stages and does not guarantee final deployment.

Why Is ByteDance Restructuring Its AI Team?

For years, ByteDance's Seed foundation model team operated in separate departments. Text specialists had their own data teams, vision researchers had another set, and so on. While this approach initially helped the company patch capability gaps quickly, it created massive inefficiencies as projects grew larger.

The result was redundant work across departments. Teams were essentially reinventing solutions in different rooms, a luxury ByteDance cannot afford when pursuing a trillion-parameter goal. To address this, the company has created four new specialized departments designed to eliminate duplication and accelerate development:

• Pretrain Data: This team now controls all multimodal data for the new Omni model, eliminating fragmented data pipelines that previously slowed progress.
• Horizon RL: This group focuses entirely on reinforcement learning, a technique that helps AI systems improve through trial and error, pushing the model's raw intelligence as high as possible.
• Product Posttrain-Work: Handles the business-to-business side, focusing on "agentic" capabilities for office tasks in Doubao and Dola, ByteDance's AI applications.
• Product Posttrain-Chat: Manages the consumer side, keeping the conversational experience sharp and user-friendly.

ByteDance founder Zhang Yiming emphasized the importance of this effort during an all-hands meeting with Wu Yonghui, head of Seed. He stated that training large models is inherently difficult and that temporary setbacks are acceptable, but urged the team to aim for the upper limits of intelligence and join the world's top tier.

How Does This Fit Into ByteDance's Broader AI Strategy?

This restructuring signals a major shift in ByteDance's approach. The company is moving away from experimental research toward industrial-scale production. The goal is no longer simply to make a model that works, but to build the biggest and smartest AI system in the room.

Zhang Yiming also advocated for integrating resources from VolcEngine, Feishu, and Doubao to build advantages in computing power and data, while cautioning against being driven solely by short-term trends. He explicitly opposed model distillation, a technique that creates smaller models from larger ones, arguing that it cannot truly surpass existing models. Instead, he emphasized that ByteDance should build artificial general intelligence (AGI) barriers from a more fundamental level.

ByteDance has also hired Guo Daya at a high salary to focus exclusively on coding capabilities, consolidating related resources to address a weakness in Seed 2.0's language model, which has received limited market traction due to weaker coding abilities.

What Are ByteDance's Recent AI Achievements?

While the 5 trillion parameter model remains in development, ByteDance has already made significant strides in multimodal AI. The company released Seedance 2.5, a video generation model, on July 31, 2026. This system can generate up to 30 seconds of video in a single request, with audio produced alongside the picture rather than added afterward.

Seedance 2.5 supports up to 50 multimodal references in one request, including 30 images, 10 video clips, and 10 audio clips, making it particularly useful for professional work where consistency matters. The model also offers timestamp-level editing, allowing users to change specific moments in a clip without regenerating the entire video. Additional features include green screen effects, camera perspective changes, reference-based editing, and clay render capabilities for spatial guidance.

At launch, Seedance 2.5 arrived on Jimeng AI and the Pro tier of Doubao, ByteDance's applications aimed mainly at the Chinese market. API access is now live through BytePlus ModelArk, with 480P and 720P output options and durations ranging from 4 to 30 seconds.

How to Understand ByteDance's AI Ambitions

• Scale as Strategy: In the AI world, larger models generally perform better across a wider range of tasks, which is why ByteDance is pursuing a 5 trillion parameter system rather than incremental improvements to smaller models.
• Organizational Alignment: By eliminating departmental silos and creating specialized teams, ByteDance is removing internal competition and concentrating efforts on key breakthroughs rather than duplicating work.
• Long-Term Investment: ByteDance founder Zhang Yiming confirmed that the company will continue to significantly increase its investment in AI, signaling that this 5 trillion parameter project is part of a sustained, multi-year commitment rather than a short-term experiment.

The reorganization reflects ByteDance's determination to compete at the highest levels of AI development. While the 5 trillion parameter model is still in early stages, the company's structural changes, leadership focus, and continued investment suggest that ByteDance is serious about building one of the world's most capable AI systems.