We got the first news about Mythos in March, so it is likely that it was already close to ready by the time Opus 4.6 was released.
So the actual gap is the time elapsed between March (or April for the official announcement) and whenever Chinese models can match Mythos.
Why would Anthropic get the benefit of pre-release models counting toward their lead, if nobody else gets to count their pre-release models?
But exactly which point in time is z.ai compared to claude.ai? Consistently bring "6 months behind" in an exponentially acellerating evolution means the gap is growing exponentially wider, not constant.
Oh? Exponentially accelerating, huh? That's quite a surprise, to me.
A couple: usually 2, though not always
A few: 3, 4, 5
Several: 4, 5, 6, or 7.
I had to explain this to my German friend. In my understanding this isn't about the actual number, it's about the certainty. If it's absolutely and definitely two, then I say two. If I'm uncertain but it's probably two, or if a non-integer, somewhere around two, then I say couple.
And few is more likely to be 3 than 5, because 5 is getting close to a "half-dozen or so", or (as you say) several.
Many is very context-sensitive, as the meme has it.
So I would agree that the open models are a few months behind, definitely more than a couple of months behind, possibly several months behind, maybe a half-dozen months or so behind, but not many months behind.
3 or 4 would likely be a few, or some. 1 is, well, one.
The gap between Chinese models and American frontier models is estimated at 10 months by Anthropic themselves, and it's growing.
China has no flywheel for long-form agentic traces like Claude Code and its telemetry over its userbase (no one uses the Chinese harnesses yet). Most Chinese models are forced to price themselves significantly below cost to compete with the huge demand for bootleg claude tokens, because they're that much worse.
How is this different than any business with something to lose saying a competitor isn't as good? Not saying it's false, but it would seem to me that it's more important how customers feel about the issue.
I don't know what I was thinking.
I've heard half a dozen people talk about how a less advanced model coupled with a better harness outperforms a smarter model in the last few weeks.
If the USA wanted to shoot its AI industry in the foot it achieved its goal.
There's a lot of subjectivity in determining this, but I'm 100% sure that 10 months is wrong.
I don't know whether the gap is currently growing, but I'm not sure it matters. There are thresholds where models reach certain levels of usefulness. Opus 4.8, for example, is at a level where I can give it relatively vague input, and it can go for half an hour on its own and produce a high-quality PR.
If GLM reaches that level of capability and can do that task more cheaply than Anthropic's model, I will use GLM for that task, because that's a specific type of task I use models for. It doesn't really matter whether Anthropic also has a better model, because what does "better" mean in this context? It's a clearly defined task, and Opus 4.8 already does it at a very high level of quality.
And you seem to think "no one uses" DeepSeek's v4, z.AI's GLM 5.2 or Xiaomi's MiMo 2.5 from their official APIs when they probably dwarf Anthropic's usage and are widening the gap due to conquering a chunk of Western market too.
I know it's hard for some to comprehend there's an entire Eastern hemisphere in the globe with billions of people, so it's worth reminding. And some seem to think the world is basically silicon valley even.
Can you comprehend than Anthropic is winning because is both cheap(subscriptions) and better SOTA. People are cheering China providers when I reality they would rugpull open weights the moment they are competive.
China models are trash that why they are giving them away for free.
For individuals and small companies subscriptions is the best deal, for big companies china models are big no unless they can host them.
HN is full of contrarians and folks who don't know what they're talking about in regards to AI.
#1 I've had use cases where it was clearly obvious the Chinese models were behind.
#2 I've also had use cases where I couldn't tell a difference at 1/20th of the price.
The problem is - the #1 is the use case where American frontier is gated behind saboteur classifiers and is tiny minority anyway. Vast majority of work is #2.
The gap doesn't matter anymore.