Free alternative to Claude Code: test drive of a local Qwen3 solution

Can a free solution replace a paid coding tool? Claude Code from Anthropic is powerful, but expensive. An alternative could be a combination of the local Goose agent, the Ollama platform, and the Qwen3-coder model. The author decided to check how viable such a replacement is in practice.

Ollama allows you to run language models locally, without the need to send data to remote servers. This is important for privacy and speed. Goose Agent serves as an intermediary, simplifying interaction with the model. Qwen3-coder is a specialized language model trained on large amounts of code. All components are free and open source.

The experiment consisted of solving a series of typical coding tasks: from writing simple scripts to debugging existing code. First, Ollama was set up, which turned out to be a fairly straightforward process. Then Goose Agent was installed and configured. The most difficult stage was setting up Qwen3-coder, which required some command-line work.

During testing, it became clear that the combination of Goose, Ollama, and Qwen3-coder handles basic tasks quite well. The model generates reasonably good code that requires minimal debugging. However, when solving more complex tasks, Claude Code proved to be better, especially in terms of context understanding and generating optimal solutions. Nevertheless, the local solution turned out to be quite suitable for everyday tasks.

What conclusions can be drawn? First, free and local solutions for code writing are becoming increasingly competitive. Second, for complex tasks, it's too early to abandon paid tools. Third, the development of open-source models, such as Qwen3-coder, opens up new possibilities for developers who want to control their data and reduce costs. This is an important step toward democratizing AI.

Overall, the experiment showed that the combination of Goose, Ollama, and Qwen3-coder is an interesting and promising alternative to Claude Code. It is suitable for solving simple and medium-level tasks, provides privacy, and requires no financial investment. However, for complex projects, it is still advisable to use paid tools. The future lies in the development of open-source models and simplifying their use.