81–90 of 160 posts
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Oh. Being buried in hierarchy does not inspire hope.
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I'm interested to see where they want to land performance-wise (i.e. which point they choose on the scaling curve) and the niche they want to carve. They have a decent ways to scale beyond trinity large, in paticular on posttrain/RL before they are competitive with open-weights, especially internationally. Deepseek is explicitly banned [1] at LLNL and I wouldn't be suprised if there's a blanket ban on all Chinese mod…
That's interesting a locally hosted LLM would be banned. I'm assuming locally hosted is included. Do they think it's been trained to sabotage equipment?
https://simonwillison.net/2026/Jun/10/if-claude-fable-stops-...
I can imagine if the US were already doing that as a safeguard, they would assume their "adversaries" (to use Anthropic language) were doing the same as well, whether that were true or not, and therefore would not trust those models even if locally hosted.
Just realized that there are basically no American open models right now ever since the Llama series was abandoned. Basically Gemma and GPT-OSS I guess? Ah but Mira Murati's new Inkling is Apache 2.0 But it makes sense that if you're a university researcher you are thinking about what's a model that will be open weight and developed over the long term and doesn't raise 'Chyna' concerns in Washington DC
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Mostly because it's generally a bad idea for government to try to compete with a brand new tech industry with hundreds of billions in private capital developing commercial models. If the American private industry does actually wash out vs Chinese open models there might be talent available for them to put money into, so maybe they are just preparing for that scenario in the meantime.
we're about witness the realization that "here's a tech that can make us a whole bunch of money" is actually "here's tech that will establish the next hegemony." american companies may compete with chinese companies on the former. only the USG can compete with the PRC on the former.
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Laguna S 2.1 is really great too, in the "preview" release they've done so far at least. Still pending some reasoning-looping, but besides that, it's a really strong model to run within 96GB VRAM with the NVFP4 variants, and it's really good at coding (specifically).
There was an obvious problem in the original release, they re issued it after like a week with the reasoning looping supposedly fixed.
Besides that, it was also discovered that their suggested inference parameters were wrong and led to worse behavior. Eventually someone discovered these works best (so if you have the issue with looping right now, try these, helps a lot for me but not 100% still) and was also what the evals used apparently: temperature: 1.0, top_p: 1.0, top_k:20
Now we're waiting for RC3 which Poolside said will come at one point, and hopefully also brings down the size again NVFP4 weights + full context can load properly again even on "smaller" hardware.
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Laguna S 2.1 is really great too, in the "preview" release they've done so far at least. Still pending some reasoning-looping, but besides that, it's a really strong model to run within 96GB VRAM with the NVFP4 variants, and it's really good at coding (specifically).
Yeah I think it got bad press because the chat templates (or something?) were messed up on first release, but I've been using a quant of it and it's a powerhouse, better than qwen 3.6 27b for local on a 3090, which is saying a lot.
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It's a lot smaller, and runs (quantized) on a 3090 quite well. Ds4 flash 0731 you're talking about? It's great but it's much harder to run locally.
I found Laguna S to be pretty good at coding, pretty fast, but pretty bad as an agent - not proactive, would frequently stubbornly argue things that weren't true, and pretty bad general knowledge. But as a pure coding model, pretty good. Deepseek v4 Flash 0731 is so much better if you can run it, though. Grain of salt, I think I grabbed Laguna after they fixed the initial looping issues, didn't notice those, but ther…
Yeah, this is my perspective too on Laguna S 2.1. Works amazingly for coding, pretty bad for pretty much anything else. I don't do a lot of advanced math, supposedly it's good for that too.
Just realized that there are basically no American open models right now ever since the Llama series was abandoned. Basically Gemma and GPT-OSS I guess? Ah but Mira Murati's new Inkling is Apache 2.0 But it makes sense that if you're a university researcher you are thinking about what's a model that will be open weight and developed over the long term and doesn't raise 'Chyna' concerns in Washington DC
There's a bunch of American open models. Inkling, Nemotron, Trinity come to mind, but I'm sure there's others.