I've played with them plenty and they're not even close as far as speed or intelligence. It's like comparing a bike to an MRAP.
replyWhat harness would you recommend for the open-weight models?
replyOpencode has been the best one for me so far.
replyHaving tried local agents just two weeks ago, the parent poster is correct: they don't come anywhere near frontier models, despite what the benchmarks state. I haven't tried Qwen 3.6 yet, but the version before it frequently got stuck even on moderately complex problems.
replySame experience for me. I think people need to start providing context for the type of work they're doing when repeating the local model hype. Maybe they're working with a cookie cutter React app and it does the job fine.
replyI work on Go and Rust mostly. The experience can be wildly different based on model, quantization, and harness. The fact that it didn't work for you doesn't mean everyone is trying to hype local models, people are getting real work done.
replyThis feels like a symptom of the definition of "real work" changing right in front of us. Some people still use AI like a copilot, cleaning up code here and there, maybe writing functions. And at the right scale, this is genuinely still real work.
replyOthers, especially startups or indie hackers, use AI like it were their end-all be-all assistant. "Hey Jeeves, go add Apple Sign In, Google Sign In to our signup pages. Also, investigate why we're not utilizing cached inputs on our AI APIs correctly. And add Maestro flows for every screen in our app. Btw check out posthog, supabase, and Stripe - is our new agent changing engagement or trial->paid conversion rates?"
And 3 hours later, you have all these done. But only if you use the right multi trillion param models.
Go and Rust is not really a type of work though. What tasks are you throwing at them?
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