Developer quits local LLMs for coding

Local coding models are hitting a "reasoning wall" where quantization and local context hacks can't compensate for the lack of dense parameter common sense.

• –Tool-calling in complex environments like Docker remains a major weakness for ~30B parameter models, leading to hallucinated fixes and context-destroying output reads.
• –The "productivity tax" of local LLMs—spending more time managing the model's behavior than writing code—is increasingly unjustifiable for professional developers.
• –Prompt caching instability on consumer hardware remains a significant bottleneck, nullifying the speed advantages of local inference during long sessions.
• –Local LLMs are being relegated to low-stakes automation and creative writing where reasoning failures are less disruptive than in systems engineering.