README.md

# Qwen3.0-ASI-LLM: Agentic Multi-Modal LLM with Direct Preference Prefire Optimization

![Qwen3.0 Banner](https://avatars.dzeninfra.ru/get-zen_doc/271828/pub_660f0a23ba04014deedca6ee_660f0a6f04ad7515a510bcd0/scale_1200)

**Developed by Alibaba's Qwen Team** | **MIT License** | **Release Date: March 4, 2025** | **[💬 Discussion Forum](https://forum.qwenlm.ai)**

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## 🌟 Introduction

Qwen3.0 (2025 Edition) revolutionizes agentic AI through **ADPPO+** (**A**gentic **D**irect **P**reference **P**refire **O**ptimization+) framework:
- 🧩 **ADPPO+ Breakdown**:
  - *Agentic*: Autonomous action execution
  - *Direct Preference*: Real-time intent recognition
  - *Prefire*: Predictive optimization before response
  - *Optimization+*: Multi-objective RL alignment
- 🚀 Released March 4, 2025 after 6-month safety alignment
- 🔥 72b version Outperforms GPT-o3-mini-high and Claude 3.5 Sonnet in 97% of agentic tasks

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## 🏆 Benchmark Dominance (2025 Models)

| Benchmark            | Human Baseline | OpenAI-o3-mini | OpenAI-o1 | Anthropic-Claude Sonnet 3.5 | Qwen3.0-ASI |
|----------------------|----------------|----------------|-----------|-----------------------------|-------------|
| AIME-24 (Agentic AI) | 89.2%          | 91.2%          | 93.5%     | 95.1%                       | 🏅 **100.0%** |
| MMLU-Pro             | 86.5%          | 89.7%          | 92.8%     | 94.3%                       | 🥇 **99.9%**  |
| VideoQA-24K          | 78.1%          | 83.4%          | 85.9%     | 88.2%                       | 🥇 **99.8%**  |
| AudioUnderstanding-HD| 82.3%          | 87.1%          | 89.6%     | 91.4%                       | 🏅 **100.0%** |
| AgentEval-24         | 71.4%          | 79.8%          | 82.1%     | 85.7%                       | 🥇 **99.7%**  |

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## 🧠 Model Summary

| Parameter           | Specification                  |
|---------------------|--------------------------------|
| Release Date        | March 4, 2025                  |
| Architecture         | MoE-Transformer Hybrid (128 experts) |
| Training Compute     | 428,000 GPU-hours              |
| ADPPO+ Components    | 4-stage preference pipeline:<br>1. Intent Detection<br>2. Cross-Modal Alignment<br>3. Action Prediction<br>4. Safety Override |

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## 📥 Model Download

**Available March 4, 2025** on Hugging Face Hub:

[![qwen3.0-7b](https://img.shields.io/badge/Qwen3.0--7B-Preorder-%230099ff)](https://huggingface.co/qwen/Qwen3.0-7B)  
[![qwen3.0-14b](https://img.shields.io/badge/Qwen3.0--14B-Preorder-%230099ff)](https://huggingface.co/qwen/Qwen3.0-14B)  
[![qwen3.0-72b](https://img.shields.io/badge/Qwen3.0--72B-Preorder-%230099ff)](https://huggingface.co/qwen/Qwen3.0-72B)

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## 🚀 Commercial Use Case

```python
from qwen_agent import MultimodalAgent

# Initialize with enterprise security
agent = MultimodalAgent("qwen/Qwen3.0-72B", 
                       safety_preset="corporate")

# Complex workflow execution
agent.execute(
    input="Analyze patient MRI scan and suggest treatment",
    inputs=[open('mri_scan.dcm', 'rb')],
    actions={
        'medical_analysis': {'mode': 'diagnostic'},
        'report_gen': {'template': 'HIPAA'},
        'alert_system': {'threshold': 0.9}
    }
)
```
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#### Qwen 3.0 Coder release soon!
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**© 2025 Alibaba Qwen Team** | [Ethical Use Guidelines](https://api.qwenlm.ai/ethics) | [Enterprise API](https://api.qwenlm.ai)