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technologyreview.com·2h ago
Data Science
Towards AI·May 26·5 min read
Claude Code Free with Local AI
TL;DR
Claude's paid subscriptions ($17–$100/month) impose context limits (maximum tokens, or units of text the model can process) that constrain work on large codebases. A five-step workflow combines Claude Code, Ollama (a local AI runtime), and open-source language models to eliminate subscription costs and expand context windows to 64K tokens.
✦ Why It Matters
Engineers can eliminate Claude subscription costs and context limits by self-hosting compatible models locally.
Key Takeaways
- Install Ollama and pull an open-source model to run inference locally without cloud costs.
- Connect Claude Code to your local Ollama instance via API configuration.
- Expand context windows to 64K tokens to handle large codebases without hitting ceilings.
- Trade cloud convenience for self-hosted control and unlimited token usage per session.
Full Summary
Claude, an AI coding assistant, requires paid subscriptions with context windows (the amount of code and conversation history a model can consider at once) that deplete quickly on large projects. This article presents a practical five-step setup: install Claude Code (the IDE extension), install Ollama (a framework for running large language models locally on your machine), pull an open-source model compatible with Claude's API, connect Claude Code to your local Ollama instance, and configure a 64K token context window (64,000 units of text).
By running inference (the computational process of generating predictions) on local hardware instead of Anthropic's servers, developers eliminate subscription costs and remove hard limits on context size. The approach trades cloud convenience for self-hosted control, enabling unrestricted work on large codebases without recurring fees.