Claude Code with Local LLMs and ANTHROPIC_BASE_URL: Ollama, LM Studio, llama.cpp, vLLM

1. 1Install Ollama or LM Studio on your local machine using the provided instructions
2. 2Configure the ANTHROPIC_BASE_URL to enable native Anthropic endpoints
3. 3Optimize context-window sizing for improved performance using the 32K context option
4. 4Test the local Claude Code with the optimized settings using the MacBook Air Gemma 4 26B-A4B Q4 or MacBook Pro Gemma 4 26B-A4B Q4 / UD-Q4
5. 5Compare the performance of different local LLM setups, such as vLLM, to determine the most efficient configuration

AI engineers and researchers can benefit from this tutorial to develop and fine-tune local LLMs, while data scientists can utilize the optimized models for various applications

💡 Native Anthropic endpoints and optimized context-window sizing can significantly improve the performance of local Claude Code with LLMs

🚀 Run local Claude Code with LLMs using Ollama, LM Studio, or llama.cpp! Optimize with native Anthropic endpoints and context-window sizing 🤖