The video reviews the mysterious and fast coding model “Cheetah,” highlighting its impressive speed and some useful outputs but also noting its inconsistent understanding, functional issues, and high token usage. While the model shows potential and exclusivity within the Cursor IDE, its origin remains uncertain, and it is considered competent but not revolutionary.
The video discusses the release of a mysterious new coding model called “Cheetah,” which the creator finds bizarre and intriguing. The model is incredibly fast, demonstrated by its ability to quickly generate a machine learning model that loads fake data and trains two versions—a linear regression and a random forest model—though only the random forest model is saved. The creator appreciates the speed and the inclusion of both models for comparison but finds the overall behavior of Cheetah unusual and difficult to pin down in terms of its origin.
The creator shares their experience testing Cheetah with various coding tasks, including building an API. They found the model struggled with understanding context and following instructions precisely, often returning incorrect or irrelevant results. Despite these frustrations, there were moments when the model produced useful outputs, such as architectural planning and automatic updates to documentation files. However, the creator notes that steering the model toward the desired outcome was often challenging, requiring multiple attempts and restarts.
One of the most curious aspects of Cheetah is its exclusivity to the Cursor IDE and the fact that it is a paid service. The creator speculates about the model’s origins, considering possibilities like OpenAI, Anthropic, Grok, or even a new entrant, but remains uncertain. They highlight a playful test where the model created a text-based adventure game that hinted at Cursor as the creator, though this is likely a random or misleading clue. The speculation leans toward Cursor potentially launching its own model, given the volume of data it could access and the precedent set by other companies.
The creator also reviews several demos built with Cheetah, including games, portfolios, and a traffic simulator. While some demos show decent design and animation, many suffer from functional issues, such as broken game mechanics or non-working calculators. The model’s style is noted for a heavy use of purple and a design aesthetic reminiscent of GLM models, though the creator doubts it is actually based on GLM. Performance-wise, Cheetah scores around the level of Sonnet 4.5 and Grok Code Fast, making it a competent but not outstanding model.
Finally, the creator points out some weaknesses, such as poor performance with Rust programming and high token consumption, which could make the model expensive to run. Despite its flaws, Cheetah is seen as a fast and capable tool, though not the best available. The video concludes with an invitation for viewers to share their thoughts on the model’s origin and their experiences using it, emphasizing that while Cheetah is competent, it is not revolutionary.