3D foundation model developer Tripo AI has closed a $150 million Series A3 funding round, drawing investment from companies across the automotive, gaming, internet, and technology sectors.
Geely Capital was among the automotive-side backers, joined by other strategic investors from that sector. Gaming companies 4399 Network, Tanwan, and Giant Network also joined the round, alongside strategic investors Fosun Capital and Orinno Capital.
On the financial side, CoStone Capital, Addor Capital, T-Capital, and Muhua Tech Ventures took part. Existing shareholders INCE Capital and Genesis Capital increased their prior investments.
Recent product releases
Over the past six months, Tripo AI has released two 3D foundation models, Tripo H3.1 and Tripo P1.0, along with two feature additions: 8K Texture Generation and Segmentation V2. The company says it has ranked among the top-performing AI 3D models in independent blind evaluations and community voting during this period.
The company also introduced Project Eden, a world model research preview. Its architecture separates the simulation of underlying state from visual rendering, a structural choice the company says establishes a new architecture for world model development.
Use of funds
Tripo AI said the new capital will go toward core algorithm development, data infrastructure, and hiring for its research team, as well as expanding commercialization internationally. Stated focus areas include intelligent manufacturing, interactive entertainment, and embodied intelligence applications.
A push toward physical-world infrastructure
This round extends a strategy Tripo AI has been building for months: moving past generating static 3D assets and into systems meant to simulate and interact with spatial environments.
That trajectory traces back to Tripo AI’s $50 million raise in March 2026, when it introduced Tripo H3.1 and Tripo P1.0 alongside an early-stage world model initiative then called Tripo W1.0. At the time, the models represented spatial data in a shared feature field rather than predicting geometry sequentially, an architectural choice the company said would produce more coherent topology than sequence-based methods adapted from language or image models.
Tripo AI is betting that this shift toward simulation-based infrastructure pays off before the broader world-model race becomes crowded. Whether that plays out on its stated timeline is something to watch.
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Featured image shows Segv2 Visual Demo. Image via Tripo AI.
