The fact that multiple companies can breach any benchmark means there is no ambiguity in terms of how to build AI, its just a matter of time.
Certainly Meta and Google are benchmaxxing to please public markets, but it still proves the above
I wonder how much is actual improvements in the model and how much comes from better harnesses. I'd be willing to bet that the combination of better harnesses + the models being trained around agentic workflows (i.e the harnesses) has made it significantly better in many things, but it's hard to find other improvements imo.
Like a working scroll on a webpage.
God damn this is impossible to use of safari mobile.
I like this phrasing and am curious what new word or phrase we might use to describe big companies over pushing Ai internally at the expense of their product quality. This pattern is so ubiquitous across google cloud products I have taken to calling them the 21st century IBM, having been a IBM baby and witnessing first hand their fall from exceptionalism.
Now, I happen to believe that's an excellent strategy. I bet they actually resolve more LLM requests than any other company at this point. The lay person still uses Google exclusively.
That was a long wait.
I've been trying it out via the API and the model has been a delight so far. Clear in the head, not RL-fried, distinct writing style, and big model smell. That said, the em-dash is back w/ this model.
That said, I would be so frustrated with Sundar Pichai if I was on the Google team. The botched rollout of this model seems to be entirely a matter of capacity, and Pichai has been more than happy to give it to anybody but his own team.
Is it actually available?
"Hans, we're doing a new point release! What isn't crossed out on the periodic table yet?"
e.g.
X: The Parameters
Y: The "System"
Z: The "Ongoing Grind"
Another quite unpleasant tick was that if you specify a peculiar term in your prompt as a conversational shortcut, it would keep repeating that throughout the conversation. e.g. "...What is a bitter lesson pilled way to do this?", then you'd see it will quote "bitter lesson pilled" at like 7 places in its response. This one seems to have eased off a little.
"Across Google", wonder how much that is because of an effort by Google to curb usage of Anthropic models. MSFT and Meta similarly are pushing for in-house models. It doesn't mean the models are better when you push your engineers to dogfood and restrict access to other LLMs.
(Not that I know for sure this is the case, it's more of a hypothesis).
fyi: argon is an interesting choice of name, coming from the Greek argos meaning "lazy or living w/out labor".
I never touch 3.8, it's awful. Curious to try this, but I've yet to use any Gemini that is good for agentic work.
Also, unrelated but this made me look at Artificial Analysis to see where it lands on Cost per Task, and it ranks Opus 5.5 at almost double Astra 6. That does not align with my experience.
Unavailable · Gemini 4 Argon is currently available to Ultra plan subscribers.
Couldn't you just say what the price will be after the introductory period and when it'll take effect? Do they have some SKILL.md for these blog posts that requires the most important information to always be buried ten levels deep and hidden behind a login page?
$2/million input and $10/million output today. $4/$20 after December 1st.
Is Elon Musk doing their pricing?
Here's low, medium, high. Even low is better than pelicans from any other lab: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
low cost 10.185 cents, medium was 11.098 cents, high was 17.166 cents.
The costs are similar because it used more output tokens than reasoning tokens for all three pelicans, even for high.
What’s the point lol. I’m not subbing to ultra to have it
Edit: noble gases not noble taxes, though the latter would be a funnier naming scheme.
This is crazy if it can work accurately.
Even after using the free model in Google search talking to Anthropic or OpenAI models feels like talking to an ox.
God knows why the server different things to the same people on different interfaces
Pretty misleading.
The code is bad though.
But on December 1st Argon doubles in price - so it will be the same price as Opus 5.5.
A more intelligent model would not default to spaghetti throwing, it would pause to consider the problem fundamentals, the accuracy of assumptions, and ask questions that remove ambiguity. This however does not lend itself to increasing token sales while prices are remain inflated from market and brand dominance.
And took similar companies that were quality engineering focused -- like DEC or Palm -- down with them through acquisition.
One possible thing : My Pro sub has been at 50% discount for the last six month, this is the very last week I'm gonna be on it.
https://one.google.com/about/google-ai-plans/?icid=microsite...
It seems to be rolling out gradually.. not available at once to everyone.
It doesn't show in the desktop UI.
> Gemini 4 Argon (Medium)
Unavailable · Gemini 4 Argon is currently available to Ultra plan subscribers.Medium and high are fixies apparently, (or they have a worm gear, although the hub doesn't look big enough for that), since neither has a derailleur. That would also explain the lack of brakes at least.
Low is still obviously failing the "test". It's pedals are not actually attached to the bike either.
Medium has a handlebar that goes through the pelican's beak. So I'd say also failing.
For the high, the only nitpick would be that the bell isn't quite on the handlebars and the stripes on his scarf don't line up correctly.
> If it's on HN and is a meme at this point, it will end up in the training set.
> It's kind of fun to imagine that there is an intern in every AI company furiously trying to get nice looking svg pelicans on bicycles.
Google listened and assigned a few interns, I guess, for the task
Modern models can make nearly photorealistic games in threejs. So why do they struggle with these pelicans?
The test is always going to be hard though, because it's an absurd image to ask for.
The pretty 3d stuff you see are agents controlling a Blender MCP in a loop where they look at the scene, think, adjust the scene, repeat.
Subtle highlights on the metal frame, sweat beads, jaunty little hat…it has style. At least compared to the rather literal ChatGPT outputs. https://static.simonwillison.net/static/2026/gpt-pelicans-gr...
username_my1•28m ago