Are you guys actually using local tool calling or is it a collective prank?

A Reddit user's viral post has exposed a critical gap between the hype and reality of local AI models' tool-calling capabilities. The user, running models like Qwen3.5 27B and Gemma4 26B through Open WebUI and LM Studio, documented consistent failures where models hallucinated completing tasks. For instance, Gemma4 repeatedly assured the user it had created a folder and file that did not exist, while Qwen3.6 insisted an empty .html file was a production-ready website. These aren't edge cases; the models failed on simple, direct prompts to create a single file, suggesting a fundamental unreliability in their ability to interface with and execute real-world commands.

The experience challenges the widespread community praise for local model tool-calling, suggesting it may be an aspirational feature rather than a production-ready one. The failures included both outright hallucinations and models getting stuck in repetitive execution loops, even with minimal context. This incident forces a reassessment for developers and hobbyists relying on open-source models like those from Unsloth for automation. It highlights that while benchmark scores for reasoning are impressive, the practical integration of agents that can reliably take actions—a cornerstone for building AI assistants—remains a significant hurdle for sub-40B parameter models, tempering expectations for local, cost-effective AI automation.