# AI-assisted Coding - FLock x Aptos LLM (outperforms ChatGPT-4o!)

**FLock’s Aptos LLM outperforms ChatGPT-4o in generating Move-specific code**, setting new standards in decentralized programming tools and allowing developers to produce secure, high-quality Move code with unprecedented efficiency. By partnering with the Aptos Foundation, FLock has created a specialized Large Language Model (LLM) that leverages community-contributed Move code to enhance AI-assisted coding on the Aptos blockchain.

This decentralized approach not only addresses the unique requirements of Move—such as resource-oriented asset handling—but also excels in tasks ranging from simple scripts to more complex applications like yield tokenization with AMM functionality. FLock’s model consistently demonstrates higher accuracy and alignment with Aptos-specific criteria compared to generalized LLMs.

Looking ahead, FLock plans to expand its dataset with expert annotations and establish rigorous benchmarks to further refine the LLM’s capabilities. A production-ready model will be deployed on FLock.’s federated learning platform, supporting ongoing, decentralized improvements as it adapts to real-time needs and incorporates proprietary Move codebases.

By integrating FLock.’s advanced LLM with the Aptos network, the collaboration enhances Move developer productivity, highlights the value of community-driven AI training, and showcases how decentralized AI can transform specialized coding tasks in the blockchain ecosystem.

Read more about the partnership [here](https://www.flock.io/blog/flockio-integrates-with-aptos-to-turbocharge-ai-assisted-move-language-coding-copilot) or explore more FLock models [here](https://train.flock.io/explore).


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