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Rahul Agarwal
Founder | Agentic AI...ย โขย 1d
You donโt need cloud APIs to run powerful coding agents anymore. Claude Code can now operate fully on your own GPU. The walkthrough from Unsloth AI shows how developers are making it happen. The actual setup is surprisingly simple. A local runtime like llama.cpp serves models such as Qwen3.5 or GLM-4.7-Flash. Then one environment variable redirects Claude Code to your localhost instance. But the real value appears after installation. The guide below explains the strange issues developers hit when running everything locally. For example, local inference can feel unexpectedly slow during repeated requests and long conversations. Model accuracy problems show up too. Many developers noticed odd outputs when running Qwen models locally. Another surprise is latency. Thinking mode improves reasoning but dramatically slows agent-style workflows and automation loops. Disabling it speeds everything up. The most interesting part is the final demonstration. Claude Code runs an autonomous fine-tuning cycle using Unsloth without relying on external APIs. Fully local execution. No remote dependencies. And it still runs comfortably on machines with around 24GB of memory. Local AI tooling is evolving quickly. This guide is a good snapshot of where developer workflows are heading. Hereโs the Link: https://unsloth.ai/docs/basics/claude-code
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