ac29

The data published in their S1 says they took a $693M operational loss in the first half of this year.

The other reasoning levels are almost always benchmarked, AA just doesnt show them in the default charts.

In my experience agents will reach for numpy for any non trivial math without being instructed

Its a paper launch, Argon took a few weeks from when it was "released" to when you could actually use it in agy

> For 5 units of 2 or 4 layer turnkey assembled boards, so long as you fit in the Grid Proto spec it's a little bit more expensive (not 10x, more like 1.3x)

Does that include the cost of parts? One of the issues I had with sourcing prototype PCBA's in the US is parts are much more expensive (not 10x, but also not 1.3x).

> Being mindful of wages is great, but eventually you have to accept that creating a job at a less than ideal wage is better than not creating any job at all.

For the employee, maybe. For the employer, it depends on how much time/money you have to put into training and what turnover is. Paying non-living wages leads to high(er) turnover because people will leave for anything better.

Yeah, I spent the last week with Deepseek Flash 4.1-1017, Kimi 3, and GLM 5.3 (and 5.3-flash). None of them were literally useless but also none of them were capable of making progress on the main project I am working on where Opus, Sol, and even Gemini Flash have all done very good work. Benchmarks might have you believe open models are only barely behind the big US labs in intelligence, but it feels much worse in practice.

> How long until China has its own chips?

There are dozens of Chinese domestic AI accelerators: Huawei, Alibaba, and Baidu all have chips, there are a bunch of smaller startups too. The chinese mainland is behind on leading edge fabrication though, SMIC only does ~7nm class since they don't have EUV.

Yeah at the point that Opus has read enough context to hand off a detailed plan, implementing the plan may not be that many more tokens.

Also having spent the weekend with the supposedly great Deepseek Flash 4.1 1017, I wonder if the people singing its praises have used recent frontier models. DS Flash feels like maybe Sonnet 4.5-4.6. Absolutely falls apart at things Opus/Sol currently excel at with low reasoning, and even has basic problems with failing tool calls, which hasnt been an issue with Anthropic/OpenAI in forever.

Could be a configuration issue with the provider I tried but honestly, I didnt get much better out of GLM5.3-flash. GLM5.3 and Kimi3 are much better but since most inference providers cant take a loss they are more expensive than just using Opus/Sol on subs, which are almost certainly currently a loss leader for their respective API offeringss.

> Huge, generational mistake for the USA to be leaning so hard into fossil fuels right now and actively trying to prevent buildout of solar and wind power.

If the US is trying that, they are failing pretty hard - 88% of new power in the US in 2025 was renewables, and 2026 is estimated to be above 90%

Openrouter does >600 trillion tokens a month and the top models shift on a daily basis. A lot of people are paying attention to new releases and even pre-releases (which tend to be free)

I'd rank Sol 6.1 only slightly behind Opus 5.5 in intelligence and both significantly ahead of anything else I've used (though cheaper/faster models are totally fine for a lot of tasks). My only real annoyance is 6.1 Sol is one of the slowest models I've used, which does make Opus 5.5 more pleasant to use.

There is a one click update in the WebUI now, no need to flash random bins

No, since that's a moving target. But the large GLM models are likely in a similar model weight class to the Opus family, just a few months behind

GLM 5.3 is roughly Opus class and is much, much cheaper