I have really been trying to get local models to work. I have tried different harnesses, tooling, skills, prompts, etc. But when I compare claude code with anthropic models or codex with gpt 5.5, vs qwen, glm or gemma and the same harnesses, the frontier models come out massively ahead. I am at the point where I just don't see the point of the non-frontier models, they waste more time than they save.
local models are 3 to 6 months behind SOTA models with the huge benefit of not needing to send all your IP to a shady third party.
If inference cost comes down (as it has been for the last few years) you’ll be able to run today’s SOTA in your laptop by the end of the year.
loading story #48281610
For agentic coding I 100% agree with you, it's worse and slower and more expensive for LARGE coding with local models. Narrow coding (like writing a specific function) is slow but viable. Regular LLM chat usage on high-end consumer hardware is competitive except on cost though. 0
0 - https://www.williamangel.net/blog/2026/05/17/offline-llm-ene...
The hosted frontier models are massively subsidized, right? I think the point of local non-frontier models is just learning at this point, so you’ll be skilled if/when the market starts comparing the actual price of the two different models.
[dead]