The user is experiencing slow performance when using Qwen3-Coder-Next (version Q6KL) for specific tasks such as searching individual functions in a codebase, which takes over five minutes despite the model's impressive throughput of 30 tokens per second during conversational interactions. The issue might stem from the lack of an indexing system that could pre-process and catalog the codebase, allowing the AI to quickly locate relevant sections for more efficient operation. This kind of system would improve performance by providing a searchable index rather than having the model scan the entire codebase each time a specific function is requested.
- Qwen3-Coder-Next
- Implement a codebase indexing solution like Sourcegraph or a similar tool that supports Qwen3-Coder-Next.
- Configure the indexer to scan and index your local code repositories for faster lookup times.
For homelab setups using Qwen3-Coder-Next, the absence of an indexing system can significantly slow down specific coding tasks. However, this does not affect other software versions or configurations directly unless they rely on similar AI-driven search functionalities.