The recent update to the open-source coding model Kimmy K2 significantly improves its capabilities by doubling the context window to 262K tokens, enabling better handling of large coding projects and front-end development, though challenges with speed, API reliability, and high costs remain. Despite these issues, the model demonstrates strong practical applications and potential, prompting ongoing exploration of providers and alternatives to optimize performance and affordability.
The video provides an in-depth review of the recent update to the open-source coding model Kimmy K2, highlighting significant improvements and ongoing challenges. The most notable upgrade is the doubling of the context window from 131K to 262K tokens, which allows for handling much larger coding projects and more substantial refactors. This extended context is particularly beneficial for coding complex features and managing bigger files, addressing one of the main limitations of the original version. However, the reviewer notes that while the model is better at front-end development, judging design quality remains subjective, and some stylistic choices may not appeal to everyone.
Speed and reliability remain mixed with Kimmy K2, especially when accessed through different providers. The model is large, with one trillion parameters, which demands robust hosting and results in variable latency and occasional API rate limiting, particularly with the Grock provider on Open Router. Despite these issues, Grock’s prompt caching feature is highly valued as it improves efficiency and reduces costs, although the reviewer experienced some frustrating API errors and capacity limits that interrupted workflow. Direct use of Grock’s API tends to offer better performance and more consistent caching compared to Open Router, which sometimes reports inaccurate context lengths and higher costs.
The reviewer showcases several practical applications of Kimmy K2, including redesigning a personal portfolio website and improving their own evaluation site, goe eval.com. The model successfully handled complex Vue 3 projects, maintained functionality across multiple iterations, and produced visually appealing front-end designs with features like dark mode and animations. While some bugs and design quirks remain, the overall output is a significant improvement over previous versions. Additionally, Kimmy K2 was tested on various coding tasks such as arena shooters, drone simulators, and Python-based pool games, with mixed results—some projects worked well, while others struggled with physics or interactivity.
Cost is a considerable factor in using Kimmy K2, with daily expenses on Grock reaching around $13, which could total over $300 monthly for regular use. This is expensive compared to other AI coding tools, but the reviewer justifies it by comparing it to their spending on multiple AI subscriptions. They express a desire for more affordable, unlimited access plans similar to those offered by Cerebras. Despite the cost, the value is evident in the ability to perform large-scale refactors and redesigns efficiently, which would be difficult with smaller context windows or slower models.
In conclusion, Kimmy K2’s update marks a meaningful step forward, especially with its expanded context window and improved front-end capabilities. However, challenges with speed, API reliability, and cost remain significant considerations. The reviewer plans to continue exploring different providers and models, including new Grock-based options and other open-source alternatives, to find the best balance of performance, cost, and usability. They encourage viewers to share their experiences and opinions on Kimmy K2, acknowledging that while it may not be perfect, it is a promising tool in the evolving landscape of open-source coding AI.