I believe the compensation part only kicks in if it’s the airline’s fault.

You may be right. As a direct result of the NATS issue perhaps not, but any second order issues once that is resolve you might be within scope.

Almost certainly not. The legislation says: "An operating air carrier shall not be obliged to pay compensation [...], if it can prove that the cancellation is caused by extraordinary circumstances which could not have been avoided even if all reasonable measures had been taken."

That gets them off the hook for even second order effects. No harm throwing in a claim though, there's no penalty for having a claim turned down.

NATS had failed once, so it failing again doesn't seem extraordinary to me.

It is however extraordinary, and there don't seem to be any reasonable measures a carrier could take to work around it.

Fair point.

CLaude, in particular, quietly, but genuinely and deliberately, overuses adverbs.

FWIW, on my Mac Studio I get ~24-27 tok/s generation between 0-16k context in - that's on the Q6_K GGUF with speculative decoding on. I have spent zero effort optimizing/improving this so far but will be trying the 4 bit MLX next (I've tended to find models drop off somewhat below 6 bit but maybe that isn't the case nowadays).

How's the compute side now, I wonder? Because while the Ultras have impressive memory bandwidth for inference, processing prompts still takes a dog's age on my M3 Ultra. I heard the M5 makes some strides forward in this area, though, and the M7 in particular promises to go a lot further.

M5 is excellent, they’ve finally gotten their own tensor cores.

Good for inference; however if you like to train, data format support and effective performance is limited (M5 Pro). Some hardware features are not exposed or extremely slow.

You’ll be fine for inference, but pales in comparison to what a RTX 6000 Pro can do for compute/matmuls/training.

4x faster prompt processing than M3 Ultra.

More likely double that, even. I think you'd still see many buyers there. You can spend like $16k alone on a RTX 6000 PRO with a mere 96GB of VRAM now..

They seem to be suffering from the supply constraints like everyone else. They phased out the higher capacities on the M3 Ultra Mac Studio a while ago, and if you order a 128GB MBP, say, you're looking at six weeks or more for delivery.

It's worse than six weeks: Apple quoted me 10-12 weeks yesterday for an M4 Max Studio (about Nov 17) December for the M3 Ultra. Planning to lock in a new model soon. I went looking for used but those are wildly expensive. Strange times. https://hard.bargains/posts/mac-before-sept-22/

Allegedly, they aren't making a big deal out of the M6 which won't have Pro, Max or Ultra configs at all, instead waiting for the M7: https://9to5mac.com/2026/08/08/apple-m7-chip-heres-why-it-ma...

Interesting, thanks for sharing.

It reminds me conceptually of the idea of using a ST:TNG replicator to just give you another replicator of your own, or asking a stereotypical genie for "infinite wishes". The genie is indeed out of the bottle in many ways.

I guess it’s more like asking the paid genie to give you a new cheaper genie.

And for a lot of non-frontier purposes these days, you can bootstrap via LLM-as-judge so your hyperspecific wakeword model or whatever can be trained with little to no human input, that aspect of it is fully terrific.

The frontier models are a replicator that can give you another replicator which specifically produces tea, earl grey, hot, when you push the single button, and does nothing else.

As well as the headline in/out changes, people heavily using agentic coding tools will want to note the 6x (off peak) and 12x (peak) increase to cache hit pricing on Pro (since cache hit can easily make up 90%+ of input on long sessions).

DeepSeek was hugely underpricing cache hit pricing before and even after this increase they're still cheaper on that metric than every other provider I'm aware of, but it will put an end to those "I used 1 billion tokens and spent $4" reports.

The problem with DS Flash/Pro is that they are extreme reasoning heavy and step heavy. Step = cache hit. Reasoning = output hit. So the impact on those price increases will be felt much stronger.

I think that Flash is still a usable model but Pro is DOA... Even before the price difference between Flash and Pro, vs the intelligence / problem solving / tool calling did not make sense. But now that gap has widen even more. And there are just too many competitors models now close to that Pro price range.

Especially when we compare that competitive models offer subscription services that easily cut down the token price by 1:10. That makes Pro especially a bad value.

We shall see what the 3th party market is going to do, but i suspect that prices will be increased. If the argument was that DeepSeek increases price as they lack capacity, a company with access to billions, other 3th party providers that need to rent and have less optimized infrastructures will increase prices. Especially if they get hit hard with people moving around.

Its like we always see the same issue with popular models.

* GLM 5.2 is good, capacity issues, API price up, subscription heavy nerfs. * Kimi K3 is good, capacity issues, API price up, subscription heavy nerfs. * DeepSeek V4 GA is good, capacity issues, API price up * OpenAI GLM 5m, 10m active users. Subscription usage is sneakily tightened more and more. * Anthropic Opus too popular, ...

That is the main issue. The AI users are people who actively easily move between companies. Pushing peak loads to each unprepared company, releasing load on the "less desired". And round we go ...

I haven’t noticed the Deepseek models being especially verbose. They’re also so cheap to run it doesn’t matter. These pricing changes are inconsequential since even 100 * ~0 is still a low number.

"quietly" is the biggest AI writing tell of Q3 2026.