Local one-shots, you say? Yep, we're there with Qwen 3.8 27B

Qwen 3.8 27B, a local LLM from Alibaba's Qwen team, achieves milestone-level coding performance on consumer hardware, with a user reporting it as the first local model that convinced them to integrate a local agent into their development workflow on a 5070Ti GPU. However, the user notes it does not replace frontier models like Claude for complex legacy codebases, and its one-shot test results are not meaningful for large projects.

I’d agree that it’s a milestone in achievable local LLM coding performance on less than extreme hardware. I’ve been running a 3-bit quant on a 5070Ti and it’s the first local model that persuaded me to properly wire up a local agent into my dev flow. However, it’s not enough to get me to drop my Claude or other frontier model sub and I don’t see it bursting the bubble . It does certainly shift the landscape in terms of how much I’d be willing to pay and what I expect in terms of quality and performance for my sub though. My experience will be different because “one-shot” tests are entirely meaningless to me for what I do. I have large projects with legacy codebases. Qwen 3.8 needs for more direction to deal with those than the like of Opus or Fable, especially when running on my constrained hardware. I’m really just using that term to reflect the post. I’m not someone who believes the dev side of LLMs is a bubble at this point, although datacenter hyperscaling and OpenAI in particular may well be.