tencent/Youtu-LLM-2B-GGUF

<div align="center">

<img src="assets/youtu-llm-logo.png" alt="Youtu-LLM Logo" height="100px">

📃 License • 💻 Code • 📑 Technical Report • 📊 Benchmarks • 🚀 Getting Started

</div>

🎯 Brief Introduction

Youtu-LLM is a new, small, yet powerful LLM, contains only 1.96B parameters, supports 128k long context, and has native agentic talents. On general evaluations, Youtu-LLM significantly outperforms SOTA LLMs of similar size in terms of Commonsense, STEM, Coding and Long Context capabilities; in agent-related testing, Youtu-LLM surpasses larger-sized leaders and is truly capable of completing multiple end2end agent tasks.

Youtu-LLM has the following features:

• —Type: Autoregressive Causal Language Models with Dense MLA
• —Release versions: Base and Instruct
• —Number of Parameters: 1.96B
• —Number of Layers: 32
• —Number of Attention Heads (MLA): 16 for Q/K/V
• —MLA Rank: 1,536 for Q, 512 for K/V
• —MLA Dim: 128 for QK Nope, 64 for QK Rope, and 128 for V
• —Context Length: 131,072
• —Vocabulary Size: 128,256

🤗 Model Download

<a id="benchmarks"></a>

📊 Performance Comparisons

Instruct Model

<img src="assets/generalagenticinstruct.png" alt="Comparison between Youtu-LLM-2B and baselines" height="260px">

General Benchmarks

Agentic Benchmarks

<a id="quickstart"></a>

🚀 Quick Start

This guide will help you quickly deploy and invoke the Youtu-LLM-2B model. This model supports "Reasoning Mode", enabling it to generate higher-quality responses through Chain of Thought (CoT).

Server Example

Enable Reasoning Mode (default):

./llama-server -m Youtu-LLM-2B-F16.gguf \
  --port 8080 \
  --host 0.0.0.0

Disable Reasoning Mode:

./llama-server -m Youtu-LLM-2B-F16.gguf \
  --port 8080 \
  --host 0.0.0.0 \
  --reasoning-budget 0

Key Configuration Details

Reasoning Mode Toggle

Controlled via the --reasoning-budget parameter:

• —Default (no flag): Enables Chain of Thought; ideal for complex logic and reasoning tasks. Response includes reasoning_content field.
• —`--reasoning-budget 0`: Disables reasoning; faster response time, suitable for simple conversations.

Recommended Decoding Parameters

Tip: When using Reasoning Mode, a higher temperature helps the model perform deeper, more divergent thinking.

📚 Citation

If you find our work useful in your research, please consider citing the following paper:

@article{youtu-llm,
  title={Youtu-LLM: Unlocking the Native Agentic Potential for Lightweight Large Language Models},
  author={Tencent Youtu Lab},
  year={2025},
  eprint={2512.24618},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2512.24618}, 
}