Artificial Confidence: You can’t repossess a download
A government nastygram took the country’s best coding model offline for everyone. What arrived the same week isn’t a frontier replacement; it’s an Opus-class workhorse you can own.
I’m in Indianapolis this week to keynote the AWS Community Day tomorrow morning; come by if you’re in town!
Last week’s thesis was that everything in AI is rented, and rented things get repossessed. This happens via a pricing email, a status page, or apparently a Commerce Department directive that lands at 5:21pm on a Friday and pulls Fable 5 and Mythos 5 offline for everyone because someone failed to genuflect properly to their feudal lord. Eleven days later they’re still dark, and the company says that’ll get fixed “in the coming days.” I am not going to rehash this.
This week’s about what the market did while the frontier sat unplugged and Twitter sat grousing.
What Actually Changed (Adjusted For Spin)
Three open-weight coding models landed since last I (graced|darkened) your inbox. Zhipu’s (ghesundheit) Z.ai shipped GLM 5.2 on June 13, live on its Coding Plan day one, offering a million-token context window, with MIT weights to follow. Moonshot shipped Kimi K2.7-Code on June 12, a trillion-parameter model under a modified MIT license at $0.95 per million input tokens. Cohere’s North Mini Code arrived June 9, Apache 2.0, 30 billion parameters. That last one matters specifically because Cohere is Canadian, which cuts against the ongoing “China bad” narrative. Zhipu, meanwhile, has been on the Commerce Entity List since January 2025: right now the industry cares a hell of a lot more that this model hasn’t been ripped away from them. Now we know that models can be turned off at the will of the US government. For some use cases that’s unacceptable, and as we know by now the internet treats censorship as breakage and routes around it; this is going to lead us to fascinating places.
We should be clear about what this trio of models represents. None of them are Fable-class; that tier is exactly what got pulled, and nothing open touches it—yet! But I ran GLM 5.2 this week, served through Baseten, against the multi-file work I’d normally hand Opus 4.8, and it’s an Opus-class contender: it did the job, it didn’t need four tries, and nobody had to approve my access once I shoved the key into my harness. Fable, for the brief window I had access, was pretty clearly going to be the big, slow, excellent frontier model you reached for occasionally. Opus has positioned itself as the model you reach for all day, and the all-day tier now has an open-weight peer that lives on hardware no angry White House letter can reach.
Follow The Money (It Went To The Landlord)
The capital people noticed before you did. Baseten, the platform I ran that model through, closed a $1.5 billion round yesterday at a valuation of up to $13 billion. “Up to,” because it’s split-priced at $11 billion for some investors and $13 billion for others, because of reasons that aren’t worth going into. That roughly triples its $5 billion mark from January, on something like $600 million of annualized revenue. Baseten doesn’t make a model. It makes the unglamorous layer that turns a free download into something that answers in production, across clouds it doesn’t own. Right now that’s looking like the most fundable pitch in AI: not the model (whose financials are, let’s say... dubious), but rather the place you run the model once you’ve decided it should be something nobody upstream can switch off.
For the record, the company that just had two models repossessed is the one I pay every month, so weigh my enthusiasm for ownable weights accordingly.
One last thing
A rented model can be turned off by someone who isn’t your vendor; we all answer to the sovereign government that controls the places we sit. But weights on your own disk are a lot more durable, and can change jurisdiction very quickly. So the number worth chasing is starting to look less like which hosted frontier tops the leaderboard, but rather what a correct answer costs on the version you host yourself, where “they turned it off” isn’t a meaningful risk factor. We’re building toward a real figure on that. Price your exit before you need it.
See you next week.
— C