RussianCow

Terra without reasoning is almost certainly going to be faster than Luna on High (which is roughly equivalent in intelligence according to AA).

That is very much not what "pump and dump" means.

My guess is nothing, and they're currently just releasing them individually as soon they're ready instead of all at once so that they hit the market more quickly. AI moves quickly enough that a delay of a couple weeks could result in significant lost revenue.

That margin just needs to be lower with LLMs than it is with only humans. In a lot of fields, that's a low bar. For example, medical professionals make a shocking amount of mistakes in aggregate.

> thinking real hard about what to say the next time they get together

LLMs can help tremendously with this part, though. Exploration/brainstorming, discovery, data analysis, etc can be made significantly easier with LLMs in most knowledge based fields.

This is my experience as well. Sol and Astra are by far the best of the models I use at following the instructions in AGENTS.md, almost to an annoying point. (But I'd rather have that problem than the inverse.)

This is clever and I can't believe I didn't think of it. I'm so used to appending "don't make any changes" to the end of my prompts.

The older Kimi K models (2.5 and 2.6) weren't bad for the time, but all of their models have had problems with overthinking. This also makes them significantly more expensive in practice than their pricing suggests, since they produce way more output (reasoning) tokens than most other models. Anecdotally, I've also had problems with all the pre-K3 models thinking themselves in circles trying to solve very simple problems that other models didn't struggle with. (I haven't played with K3 much because it's just too expensive.)

Borrow checker aside, I would like to think that its type system inherently makes it safer than a language like C.

I 100% agree and am a big fan of DS V4.1 Flash in general for this reason, but I'll add my own caveat: Sol 6.1 isn't far behind on completion time for tasks because it's so damn efficient. I regularly get ~300 tokens/sec with DeepSeek Flash, but it spends the majority of that time thinking and executing slow commands one by one, whereas Sol thinks less and is much smarter about the commands it runs, resulting in far fewer turns to get the same thing done. For highly agentic tasks, DS might only be ~25-50% faster, not 500% as the TPS may suggest.

(But to be clear: 25-50% faster is still a big win in my book.)

But we're not comparing a Claude subscription to using Claude at API prices; we're comparing it to using a cheap model like DeepSeek V4.1 Flash at API prices. If I hit the 5-hour limit in 2 hours with Claude and have to wait 3 hours for it to reset, I get less value out of that subscription than I would have if I'd have just used DeepSeek to begin with, and the latter isn't more expensive.

So my original point about the limits being awkward still stands.

I tried it but it's way too slow for me. DeepSeek V4.1 Flash is an order of magnitude faster, and the modest difference in intelligence isn't worth it to me for most use cases.

This is my experience with all MiniMax models: They're good on paper but fail to live up to expectations in practice. IMO, at no point has any MiniMax model been the superior choice over others, all things considered.

I don't understand what you're saying. If I hit my 5-hour limit in 2 hours, I still need to get work done for the other 3. I'm not going to sit there and wait for my limit to reset.