Dmind 1

🚀 DMind-1: A Specialized Web3 Expert Model

DMind-1 is a domain-specialized large language model (LLM) fine - tuned for the Web3 ecosystem. It addresses the limitations of general - purpose LLMs by achieving strong improvements in task accuracy, content safety, and expert - aligned interaction, making it a robust foundation for intelligent agents in Web3.

🚀 Quick Start

4.1 Model Downloads

4.2 OpenRouter API (Coming Soon)

Documentation for API access will be available soon.

4.3 OpenRouter Web Chat (Coming Soon)

Web chat interface documentation will be available soon.

✨ Features

DMind-1

DMind-1 is a specialized Web3 expert model based on the Qwen3 - 32B base. It has the following key features:

• Comprehensive Domain Expertise Data: In the first stage of fine - tuning, it underwent Supervised Fine - Tuning (SFT) on 13,276 expert - curated knowledge items from 32.7GB of Web3 documentation. Low - Rank Adaptation (LoRA) was used during SFT to internalize specialized Web3 knowledge while preserving general - language capabilities.
• Reinforcement Learning from Human Feedback (RLHF):
  • Reward Model Training: A domain - specific reward model was trained using preference - ranked outputs from human experts in diverse Web3 scenarios.
  • Policy Optimization with PPO: The Qwen3 - 32B was fine - tuned using Proximal Policy Optimization (PPO) guided by the trained reward model. LoRA ensured resource - efficient parameter updates.
• Domain - Aligned Reasoning and Interaction:
  • Natural Dialogue Fluency: It can have coherent, context - aware conversations on complex Web3 topics with strong multi - turn consistency.
  • Complex Instruction Following: It can reliably execute multi - step instructions and conditional logic, supporting agent - driven workflows.
  • Safe and Compliant Content Generation: Its outputs comply with domain - specific safety, ethics, and regulatory standards.

📚 Documentation

Introduction

The growth of Web3 technologies like blockchain, DeFi, and smart contracts requires specialized AI LLMs. General - purpose LLMs often lack domain - specific accuracy and reasoning. DMind-1 is introduced to address these limitations. It is fine - tuned for the Web3 ecosystem and outperforms general - purpose models in task accuracy, content safety, and expert - aligned interaction.

2. Evaluation Results

DMind-1 and DMind-1 - mini were evaluated using the DMind Benchmark. A cost - performance analysis was also conducted. DMind-1 achieved the highest Web3 score with low token input costs, and DMind-1 - mini ranked second, retaining over 95% of DMind-1's performance.

3. Use Cases

• Expert - Level Question & Answering: Provide accurate answers on blockchain, DeFi, smart contracts, and other Web3 topics.
• Compliance - Aware Support: Assist in drafting or reviewing content within regulatory and legal contexts.
• Content Generation in Domain: Produce Web3 - specific blog posts, documentation, and tutorials.
• DeFi Strategy Suggestions: Generate insights and recommendations for DeFi strategies.
• Risk Management: Suggest risk - management strategies based on user risk profiles.

📄 License

• The code repository and model weights for DMind-1 are released under the MIT License. Commercial use, modification, and derivative works are permitted.
• Base Models: DMind-1 is derived from Qwen3 - 32B, originally licensed under the Qwen License. Ensure compliance with the original base model licenses when using or distributing derivatives.

Contact

For questions or support, please contact team@dmind.ai