About this video
The era of Claude dominance is coming to a violent end as new open source models take the lead. In this video, I dive deep into a head-to-head comparison between GLM 5.2 and the brand new Kimmy K2.7 Code to see which one truly reigns supreme in a real world coding environment. Key takeaways include: - A comparison of GLM's 1M context window versus Kimmy's visual reasoning capabilities. - A live demo of 'Agent Swarms' propagating design changes across a full application. - Real world testing of filtering and sorting functionality built entirely by AI. - An analysis of the monthly pricing structures and which plan offers the best value for developers. - Why these models are finally reaching a level of trust comparable to the top tier proprietary systems.
Open source AI models are no longer the underdog: they are the new standard for professional developers.
The landscape of AI assisted coding is shifting beneath our feet. While many developers are still tethered to the familiar names, a new wave of models like GLM 5.2 and Kimmy K2.7 Code are proving that the gap between open source and proprietary giants is closing rapidly.
The Contenders: GLM 5.2 and Kimmy K2.7
In my latest testing, I pitted these two heavyweights against each other to see which could handle a real world codebase refactor. GLM 5.2 brings a massive one million token context window to the table, whereas Kimmy K2.7 Code counters with integrated visual reasoning capabilities.
Key Performance Markers
One of the most striking features of the Kimmy Code environment is the use of 'Agent Swarms'. Unlike traditional sequential processing, this allows multiple agents to propagate changes across an entire website simultaneously. In our test, it successfully updated design aesthetics and added complex filtering to a leads list with minimal friction.
Visual Reasoning vs Context Size
The debate often comes down to what you value more in your workflow.
- GLM 5.2: Ideal for massive projects where keeping the entire codebase in context is vital.
- Kimmy K2.7: Perfect for front-end developers who need the model to 'see' and reason about UI components.
The Verdict
We are reaching a point where these models are hitting the 'Opus 4.5' level of reliability. While they may still require focused tasks rather than broad, sweeping back-end overhauls, they are more than capable of handling professional grade front-end work.
If you are looking to modernise your workflow and potentially save on subscription costs, these models deserve a permanent spot in your terminal. We are no longer just 'dabbling' with AI: we are deploying it.
Transcript▾
GLM 5.2 has just dropped alongside Kimmy K2.7 Code, and there is a lot of debate regarding which one is actually the best. Today, we are going to settle that. I have already done a video on GLM 5.2, which apparently has better design capabilities than Fable, but I will leave that for you to decide. Let us jump into Kimmy K2.7 Code, a code-specific model, to see how it fares.
It is currently available via API or Kimmy Code. Kimmy K2.7 is a visual model, meaning it can process images, whereas GLM 5.2 is text-only but offers a much larger context size. I do not do a massive amount of visual parsing, but it is a useful tool to have.
Looking at the pricing, the 'Moderate' plan is roughly 15 dollars a month, while the 'Pro' choice for daily coding uses terms like 'Allegretto' or 'Allegro'. I am not sure why they use Italian music terms, but we will subscribe and test it out.
I am using a lead capture form where GLM 5.2 previously left off. The goal is to redesign the template detail page with modern aesthetics without changing the functionality. Kimmy Code seems to have been built from the ground up rather than using the Gemini CLI. I will enable 'auto permission mode' and 'plan mode' to see how it handles the task.
The context window is already quite high, so I will need to be careful and clear it after every task. Interestingly, Kimmy creates plans automatically and even utilises 'agent swarms' to work on multiple pages simultaneously.
The redesign is functional and looks quite good. I have also asked it to add filtering to the leads list by name, status, and company. Despite hitting some rate limits, the 'agent swarm' successfully propagated the design changes and filtering across the site.
Comparing the two: it is neck and neck. GLM has the 1M context window, but Kimmy has visual reasoning. Both are reaching a level of performance where you can actually trust them to do professional work. They are perfect for focused tasks or refactoring code originally put together by models like Opus. Overall, both are fantastic tools for any developer's arsenal.