
About
Fabian Klemm | Large Models, Small Resources: Customizing LLMs
The Germans just Frankensteined DeepSeek’s R1 and V3 into something called R1T Chimera.”
Beyond this post on X, the DeepSeek-R1T and R1T2 Chimera models published by TNG have gained significant attention, with daily usage exceeding 10 billion tokens on OpenRouter.
So, what kind of “Frankensteining” is going on here? How can a small software consultancy such as TNG produce its own models?
An internal AI research group within TNG has been experimenting with and publishing research on mixture-of-experts (MoE) large language models (LLMs).
The team started by manipulating the way experts work within a model under the name “Mixture of Tunable Experts.” It then continued with an assembly-of-experts model-merging process, which resulted in the Chimera models. Since then, TNG’s research team has been working on various ways to adapt state-of-the-art LLMs.
In this talk, Fabian Klemm provides technical insights and reviews the most important results. He demonstrates how the models were engineered and shares anecdotes about the successes and setbacks encountered along the way.