Скачать или смотреть Tencent’s Youtu-LLM: The 2B Model That Codes Like a Giant (Agentic Workflow) 🧠

We usually assume that to get advanced reasoning, we need massive, power-hungry models. But a new release from Tencent’s Youtu Lab is challenging the "bigger is better" myth. In this video, we break down Youtu-LLM, a "pocket rocket" AI with under 2 billion parameters that mimics the complex reasoning of its massive cousins.
In this video, we cover:
1. Trained, Not Distilled Most small models are "distilled" (simplified copies) of larger models. Youtu-LLM is different: it was built from scratch on 11 trillion tokens.
• The Curriculum: It moved from common sense to complex STEM, finally training on "agentic trajectories"—data that teaches it how to think and use tools, not just what to know.
2. The "Agentic" Chain of Thought Standard models use a linear train of thought (if one step fails, the whole output fails). Youtu-LLM uses a 5-Step Cycle: Analysis → Planning → Action → Reflection → Summary.
• Why this matters: The model can self-correct. It reflects on its own actions to see if they worked before moving forward.
3. The Coding Test: Battleship in C We stress-tested the model with a complex prompt: Code a playable Battleship game in pure C with a terminal interface.
• The Result: It produced a fully functional file that compiled without a single error on the first try.
• Efficiency: It handled this massive task while consuming just over 9GB of VRAM, showing impressive efficiency for long-context generation.
4. True Tool Use Beyond coding, we tested its ability to interact with external systems. We defined a get_weather function, and the model correctly interpreted natural language to generate a perfect, machine-readable tool call.
The Big Takeaway: With a 128,000 token context window and "Dense Multi-Latent Attention," this model proves that sophisticated, self-correcting AI can run efficiently on local hardware.

Support the Channel: Do you believe agentic loops are the key to smaller, smarter AI? Let us know in the comments!

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