AI surveillance might have a solution for that petty crime soon. I hope I'm wrong.

Why would you hope you're wrong?

I would be very happy if it ends up being used for petty crime vs. e.g. monitoring political dissidents.

I'm running it in router mode, but people on Reddit were recommending people use llama-swap instead. Am I missing something by using router mode?

I believe it's useful for running multiple llama.cpp forks at the same time (e.g. a model you want requires special patching)

Poolside Laguna was quite good too (if you look beyond some of the teething issues).

Had Deepseek V4 Flash 0731 not launched, their latest Laguna release was really intelligent at non-coding tasks and it would have been my go-to model for my local workloads.

For me Laguna frequently slightly corrupted text then it would be unable to notice the difference and get stuck making the dumbest conclusions. Thinks like typoed directory or function names. It was a great model other than that, but I ended up just going back to Qwen3.6

Make sure you've got the latest updates - both Poolside and Unsloth updated about a week after release, and that you're running via llama.cpp (I've noticed on the same model and same command line arguments, ik_llama.cpp loses quality for me).

Also just in case you didn't see it, Laguna S 2.1 was having issues on MXPF4 but people on Q4 and Q6 couldn't repeat the problem.

I just downloaded the latest llama.cpp and poolside Q4 and within 10k tokens it corrupted "Use ~/p/kevincox.ca as a reference" into "kevinc.ai" and then starts doing stupid things because the directory "doesn't exist".

In previous testing the Q8 was better but still had the same problem frequently enough to be very difficult to use. I don't know if it is a runner bug or model bug but at least with llama.cpp this seems to always happen and I haven't seen an issue like this with any other model.

Wow that's weird. I have it running sometimes at least 8 hours straight on a single prompt and no weirdness.

Could it be something weird like you're hitting your compaction limit?

No compaction happened. (That is set near 256k.) It seems to really not like my domain but I've seen it for various things as well (especially high-entropy tokens). Dropping random characters or various things. I've tried various flash attention and context quantization settings but nothing seemed to resolve it completely.

Continuing to build my olive oil tracking site (https://www.extravirginvault.com/) and pipeline. Freshness is king in the world of olive oil, and I hope to highlight to people they can find high quality, fresh olive oil produced near them.

It's been received well from producers and olive oil enthusiasts (e.g. looking for specific chemistry, cultivars and similar oils) but I feel like I've been shadow banned from Google - I seem to get more traffic from DuckDuckGo and Bing.

I'd imagine the Google issue may be to the fact that your URL looks like it would be porn.

I hope you're joking.

Definitely a plausible possibility

I mean I was personally disappointed here

Site was excruciatingly slow to load, locked up my browser and I just had to bounce. iPhone chrome. Likely google penalty.

Thankyou. Sorry to hear it locked up your browser. That definitely sounds like a bug - I've got GPT 5.6 Sol on the case...

Very nice site but small dataset on producers, only 2 from Spain that produces about 50% of the Olive Oil in the planet

Thanks - I'm saving the biggest and oldest producers like Spain and Italy till last so I can do them justice.

Why risk it either way if they provide weights for others to run this?

Am I being overly cautious not wanting to send my data to Chinese companies?

Your safety is more at risk with your data in the US government's hands.

If he bans them, they'll just show up as torrents. Or we'll download them from Chinese hugging face.

Over Dario's dead body.

At least Sam have us a nice model last year with the gpt-oss family.

At 1.5 bits per weight it'll still be over 500gb - that's still not running on consumer hardware.

Best case they release smaller models. 120b class of qwen 3.8 would be incredible - it fits on device for those serious about AI, but without millions of dollars in hardware for terabytes of VRAM