Local models are meaningfully useful* for agentic work now. This is a realization I came to over the last day or so.

I wrote a lot of custom mods for a game that recently switched engines. The migration is going rather smooth for most people because of wise architectural choices from the dev early on, and because they prioritized backwards compatibility in the update. But there are still some rough edges, especially if you had your hooks deep into the engine.

I recently vibeforked Unbiased Bob’s fork of Strata to make it compatible, easy to use and optimized for my OS and hardware (NixOS 5800x3d 64gb, 7900xtx 24gb). Sol 6.1 got it working with Qwen 3.8 Flash Next IQ3 XSS (~75GB) at roughly 46tps 164k ctx with enough headroom to launch a heavy browser along with a triple-A game set to low in 720p for testing when I need to (plus space for zram swap)

I set it up in deepseek harness, gave it a 14MB error log in the game’s working directory, then went to sleep. I woke up and it had run for 3 hours. The game launched with only two errors, which it quickly fixed from the new, vastly smaller logfile.

It hammered down every issue, making changes across 30 separate mod repos. Practically a one-shot, and all the features worked as originally intended.

I left a local coding agent running completely on its own for three hours across multiple repos across a dozen auto-compactions with a log file and no ability for it to verify its work besides a compiler. And it produced meaningful results. I can’t speak to the code quality, but it worked. This was completely unthinkable even just two years ago. Even one year ago, the cloud frontier wouldn’t be able to do this on its own, and now a local model can, running on my consumer gaming hardware from one or two gens back.

“Huh… So… We’re here now…" I said to myself, with a bit of stunned disbelief, wondering what the future one or two years from now might hold.

  • ImgurRefugee114@reddthat.comOPEnglish
    41·
    2 days ago

    It’s really hard to tell because I didn’t even see it getting to this point. I’m running a 75 gigabyte model on a 24 gigabyte GPU and my friend with a 16 gigabyte GPU is actually getting better performance than me. Mostly just because it’s a mixture of experts and Strata’s storage tier caching works well.

    I don’t think it’s saturated because we would have to, not quite saturate, but definitely wring out a lot of the gains from kernel and model architecture first before raw compute becomes a limitation.

    I expected this approach to AI to plateau before now. There has also been evidence that scale is not the sole key, and that quality and approach and harness all play significant roles. I thought it would have died by now, but since it hasn’t, I suspect it still has a long way to go. Given that I couldn’t have predicted this a year ago, I don’t think I can predict a year from now.