Shizhi AI
A neutral and open AI open-source model and agent community, officially said to gather thousands of open-source models, datasets, code resources and hundreds of agents, and provide supporting capabilities such as Model-as-a-Service, GPU training, image management and AI application spaces.
Updated: 2026-10-26
What is Shizhi AI?
Wisemodel, the official positioning of Shizhi AI, is an open AI model and agent ecosystem platform, described as "gathering high-quality global AI models, datasets and agents to build an open and win-win AI innovation ecosystem and social community". The official website lists thousands of open-source resources, hundreds of AI agents and hundreds of cooperative institutions. Different from warehouses that only focus on model downloads, it integrates training computing power, MaaS services and an application market.
Who is it for?
- Developers looking for Chinese open-source models for secondary development: complete retrieval, download and trial running on a single platform.
- University scientific research teams: Use the platform's computing power for model fine-tuning and experiments to avoid long waits for on-campus resources. The platform is also said to provide resources and collaboration access for enterprise R&D teams.
- Technical leaders of small and medium-sized enterprises: Evaluate the ready-made capabilities in MaaS and the Application Space to reduce investment in independent research and development.
- Model Contributors: Publish your own models, datasets and agents to the community to gain exposure and feedback.
- People who follow AI industry trends: Track the progress of the open-source ecosystem through the Information Center.
Key features
6Open Source Resource Library
The official statement says it brings together global open-source models, datasets and code resources, with thousands of them available for developers to search and download.
Agent World
The official platform states that it has established an AI agent community to centrally display and facilitate exchanges about agents available on the platform.
MaaS Model as a Service
The official provides Model as a Service capabilities, allowing users to call models without building their own environments. The official states that this service is targeted at teams that wish to quickly verify effects, and they can choose models of different scales as needed.
Computing Power Platform
The official provides GPU training services for model fine-tuning and training tasks, reducing the cost of purchasing hardware equipment.
Image Hub
The official states that it provides Docker image management, making it convenient to package and reuse the operating environment.
Application Space
The official platform states that it provides an AI application marketplace for showcasing and acquiring applications built based on models. It also mentions that the information center synchronizes model releases and community activity information within the ecosystem.
How to use Shizhi AI
- 1First, clarify the specific open-source licenses and commercial use restrictions of each resource, as the license terms of different models vary greatly.
- 2Conduct small-scale verification using the platform's computing power before expanding; once training tasks are scaled up, costs will rise rapidly.
- 3The quality of community resources varies; before downloading a model, check if the download count, update time and supporting instructions are complete.
- 4For resources related to datasets, confirm the source and compliance, and avoid using unknown corpus to train commercial models.
- 5Back up the models and data bound to your platform account, and do not keep your important assets only on a single platform.
Traffic & popularity
Data month Sep 2026
Shizhi AI receives about 1.4K visits per month and ranks #13,695,201 worldwide.
Monthly visits
12 monthsTraffic sources
- Direct39.7%
- Search33.7%
- Referrals10.6%
- Social6.2%
- Mail3.0%
- Other6.7%
Top countries
- United States31.5%
- Taiwan, China27.3%
- India14.5%
- Brazil10.8%
- Hong Kong, China10.7%
Estimated from third-party traffic data.
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