pietz

Any open weights model is "on prem".

I mean no disrespect but these are terrible numbers or am I missing something? It seems like Mistral continues to only be relevant for people that want a model trained in Europe. Too bad.

This should have been a prompt.

I know companies benchmaxx, but after what Google pulled with Gemini 3.8 Flash, I give zero f*cks about any numbers they report. No other model on Artificial Analysis dropped harder after they adjusted their weighting. Just look at their DeepSWE scores and then try to do any serious coding with the model.

Google is desperate. They haven't been performing in half a year. It's clear their researchers have been forced to integrate existing benchmarks into their training.

These numbers are meaningless. Shame on them.

In all fairness though, OpenAIs $200 plan was actually 20x compared to Plus, whereas Anthropic pulled this shady wording where it's only your session limit that is 20x while your weekly is only 10x.

But yeah, weird timing after a meh release and their competitor killing it right now.

Companies like OpenAI or Anthropic could offer it basically for free as an extension to their existing models. You still need the generator, but having something fast (and maybe even local) to do browser nav would be awesome.

In all fairness, this would be one of the better use cases of Jev I've seen.

Apparently I have a new favorite benchmark. Honestly, this is cool.

I'm surprised something like Jev came out "so late", but the hype has been ridiculous. Yes, it's a good idea. No, it only helps when fast and cheap are important and I guarantee existing labs will have this figured out in a matter of days.

Add visual understanding, add reasoning and bring down the size to run on my computer. That's when it will be interesting.

So many people that don't understand the tech jumped on the hype train because "it cannot hallucinate" and else. It's crazy.

Wow, this couldn't have been written at a worse time. OP absolutely doesn't know what he's talking about.

Looking at AA and Vals, your theory seems to check out.

My main argument is that if you want my attention in a world where an AI agent can build me a native iPhone app in 30min, you need to do better than showing me a to do list app in the hero of your landing page. Your comparison doesn't hold at all. This is not a tutorial page called "first steps", it is the first showcase of what is possible with it.

Anyway, it's fine for us to just disagree here. You just sound like someone that likes to argue for the sake of arguing, and just like to do apps, I don't have time for that.

I don't think there is demand for this framework in the first place.

- Cross platform frameworks are starting to become an anti pattern these days

- Hello world examples are losing relevance when I'm not the one writing code

- A To Do list is just the absolute least impressive thing you can showcase

From a marketing perspective, I want to showcase something that other frameworks cannot do and "this only took 10 lines of Python code" is a very weak sales pitch in 2026.

Because it's literally the least impressive thing you can build and in a world where I don't write the code anyway, a "hello world" example has lost its place (at least for human viewers).

Using a to-do list app as the first example to advertise a new app framework is absolutely wild in Q3 2026.

Thanks for the hard work, but the Tahoe limitation for the GUI app is absolutely ridiculous.

Not someone. Their single competitor. During a time when they were validating their newest internal model. What would you have done?

Truly, if this is the biggest criticism left, they should be celebrated. While in reality, all of this has a bitter aftertaste.

So weird.

Are there still any reasonable arguments to be mad at OpenAI at this point? Looking at how everything unfolded, this seems to have hit them way harder then they deserved.

That doesn't reject my claim. They just didn't name them in this post. It feels like, you're going through great lengths reading something into this.

Because that’s the one Anthropic was rumored to have solved.

Why in the world is that fishy?

Isn't that exactly what almost everyone would do given that they wanted to see how capable their model is and the tense competition they have with Anthropic right now? Stealing impressive headlines from your competitor is pure gold.

I find the claims from OpenAI somehow more relatable and reasonable.

- They threw compute on a problem another team/company was rumored to have solved to see what their secret model could do.

- The texts I read do make it seem like OpenAI wanted to talk and share credit generously.

- Imagine working on a frontier math problem with someone at Anthropic and not only do you use Codex but also through a non-business account that allows training on your data.

- Timeline-wise, if they mainly used GPT 5.6 it's unlikely any meaningful data made it into an model that's being internally validated right now.

Isn't that *exactly* the type of solution you'd expect from AI?

Move 37 comes to mind.

In case someone is asking: THIS is what a launch article should be like. 10/10.

Mission accomplished. That's both cool and fast.

I know everyone is benchmaxxing but this one feels one step too far. Doesn't DeepSWE have both public and private tasks? I'd love to see the diff here.

It looks more like Google execs losing their mind and pressuring researchers to put DeepSWE directly into the training set.

That's not being debated here. The initial reported numbers were false and this was simply pointed out. You're changing the subject.

The irony of this article being fully AI generated...

Anyway, it's over for Perplexity. They never had a great a product and the only reason for using them, was when they offered Pro accounts for free. Many people joined. Me included. But with a "meh" product and the general AI business not being very sticky, they lost quite harshly.

I thought they might be able to make money as a search api/index, but this article closed the book.

I'm not convinced an unstructured collection of memory files is the way to go at all.

Appreciate you taking the time. That fable analogy is well put. Almost obvious once you know it.