Kimi K3 China's 2.8 Trillion Parameter AI Just Dethroned Claude!

Kimi K3 China's 2.8 Trillion Parameter AI Just Dethroned Claude!

A new 2.8 trillion parameter model from China is officially outperforming Claude on key AI benchmarks. Get the facts on this release.


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🔗 Resources & Links Mentioned

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Plus, we cover the Friday 3 PM developer log habit, why you should always be interview-ready every six months, and answer a listener question about how to handle recruiters before your first interview round.


✅ If you made it to the end, comment: “Better talking points!” so we know who is a real one!


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Danny Thompson

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www.DThompsonDev.com


Leon Noel

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https://www.linkedin.com/in/leonnoel/

https://100devs.org/


📧 Have ideas or questions for the show? Or are you a business that wants to talk business?

Email us at dannyandleonspodcast@gmail.com!


This episode of The Programming Podcast breaks down the specs of this massive Chinese AI model. We analyze why it matters that this is the first open-weight AI of this scale to compete at the top of the leaderboards. If you follow the rapid advancement of large language models, this update is critical for understanding the shifting competitive landscape.


We discuss the technical implications of a 2.8 trillion parameter model and what its open-weight status means for developers globally. You will walk away with a clear understanding of how this Chinese AI model compares to current industry leaders like Claude and whether it truly sets a new standard for performance.


Subscribe for weekly AI and programming breakdowns, and comment below if you think open-weight models will overtake proprietary systems this year.


Chapters

0:00 - Intro & The 2.8 Trillion Parameter Breakthrough

A look at Moonshot’s Kimmy K3, the first frontier-level open-weight model, and why its release is a massive moment for the AI space.


2:04 - Sponsor Segment: GitKraken

3:26 - Open Weights, Privacy, & Breaking the Monopoly

9:00 - Real-World Testing & Token Optimization

17:48 - Beyond Code: Omniscience & Context Engineering

24:04 - AI Swarms & Cloning MacOS

29:37 - Community Win: Landing an IBM Job with AI

33:17 - Q&A: Navigating the Salary Target Question

41:38 - Outro

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