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This announcement also mentioned that they will release the next version (official non preview version) of v4 in mid July.

Is it only the Indian government? I don't think that's in any way unique to India, I've seen many poor government websites.

Ah got it. Reread previous comment and that makes sense.

Sol? Looks like openai is jealous of anthropics good model naming ability and wants to emulate it.

Hmm your last sentence seems to exactly agree that it's a class of algos that parallelize well? What does sped up arbitrarily mean? It's still polynomial speed up right?

So is it a class of problems that can be parallelized well?

Does that support modern gaming?

I read quite a few posts about this on RedNote.

That's not true, some of them are indeed fake, but a lot of them are actually providing real opus at low cost doing what op said.

Even as a GLM z.ai fan, I wouldn't pay for their plans. They are just way worse values than gpt or anthropic plans, in terms of both usage and capabilities.

If AI is so good, then why don't we have perfect compatibility layers between OS's for games yet?

The official API is FP8, which should imply that it's lossless.

There are definitely some Chinese bots + actual people (imagine that!) who like to talk up Chinese models, I'm one of them but I like to find out how good these models really are before saying anything.

GLM definitely isn't opus level yet but it's for sure good. I think it lacks some knowledge (when coding) that the frontier models possess, which is expected given that the model is probably quite small when compared to the frontier.

But people don't say much about Mistral, probably because they are nowhere as good.. And they don't have large population behind them to actually use them.

Fun fact: Zhipu aka Z.ai, Knowledge Atlas etc., the company that made GLM, is listed on Hong Kong stock exchange, is up over 10x since the IPO at the beginning of this year.

I indeed got a few timeouts yesterday using the official API, I imagine for the coding plan users it'll be even worse.

Many other open source models have vision but they don't compare to GLM in terms of coding quality. So I don't think it's because of vision that the frontier models are better, it's more that they are probably just much bigger models.

I don't know what people mean when they say design lol, is it for frontends?

Given that DeepSwe is one of the very few coding benchmarks worth taking a look at, this achieves rather excellent result at it (not far from opus 4.8).

From looking at the results and my own impression of 5.1 and other models, I think this is the best Chinese coding model by some non-insignificant margin.

Given that DeepSwe is one of the very few coding benchmarks worth taking a look at, this achieves rather excellent result at it (not far from opus 4.8).

From looking at the results and my own impression of 5.1 and other models, I think this is the best Chinese coding model by some non-insignificant margin.

Well, the level of tech is at least on a whole different level at those companies than whatever cohere is doing.

Hmmm no? The only way is to deploy your own local model, using anyone else's you are at their whim on what happens to your data.

And notable absence of DeepSWE benchmark where they do badly, but somehow a benchmark that was published yesterday is in this announcement.

But I think the eventual goal is that documentations won't even be needed. LLM should just itself understand the nuances of frameworks by analyzing their codebase.

I think Jane Street is an Anthropic investor, so take it fwiw.

Yeah I guess it being vague is more what I meant. But even if you told AI you need to wash the car, then why are you asking AI in the first place whether you should walk there or drive there. The question just doesn't make too much sense to me, doesn't look like it makes sense to the AI's either.

Meh, I feel that the car wash test is probably the worst question of all of those LLM test questions. The question is basically logically inconsistent and expect the model to work around the inconsistency.

For coding I wouldn't say a year, last year this time claude or gpt definitely weren't able to do what GLM is able to do today, but easily 6 months I'd say.

Not sure about other domains though.

Reality has both negatives and positives. Gamers Nexus clearly lie on the other side of the spectrum where they overwhelmingly choose the negative stuffs, hence rage baits.

I understand their points. But to me they do too much rage baits these days that I can't bring myself to watch their stuff. Why would I let my self get angry lol.

Even last year at this time people wouldn't believe it.