Simultaneously, we also hype up the open models that are catching up. That are significantly more discounted, that also put pressure on the big players and keep them in check.
People aren't falling for PR; people are encouraging the PR to put pressure on the competition. It's not that hard.
Here and on AI tech subreddits (ones that aren’t specifically about local or FOSS) seem to have this dynamic, to the degree I’ve suspected astroturfing.
So it’s refreshing to see maybe that’s just a coincidence or confirmation bias on my end.
Thanks!
It makes using my Claude Pro sub actually feasible: write a plan with it, pick it up with my local model and implement it, now I'm not running out of tokens haha.
Is it worth it from a unit economics POV? Probably not, but I bought this thing to learn how to deploy and serve models with vLLM and SGLang, and to learn how to fine tune and train models with the 128GB of memory it gets to work with. Adding up two 40GB vectors in CUDA was quite fun :)
I also use Z.ai's Lite plan for the moment for GLM-5.1 which is very capable in my experience.
I was using Alibaba's Lite Coding Plan... but they killed it entirely after two months haha, too cheap obviously. Or all the *claw users killed it.
So I agree with you, its better than Sonnet but way cheaper. I do wonder how long that will last though
Most recently I used it to develop a script to help me manage email. The implementation included interacting with my provider over JMAP, taking various actions, and implementing an automated unsubscribe flow. It was greenfield, and quite trivial compared to the codebases I normally interact with, but it was definitely useful.
The TL;DR is that unless you are doing it as a hobby or working in an environment where none of the data privacy options supported by Anthropic/OpenAI (including running on Azure/Bedrock with ZDR) work for you then it's not worth it.
The best open models are around the Sonnet 4.6 level. That's excellent, but the level of tasks you can give to GPT 5.4 or Opus 4.6 is just so much higher it doesn't compare (and Opus 4.7 seems noticeably better in my few hours of testing too).
I have my own benchmarks, but I like this much under-publicized OpenHands page: https://index.openhands.dev/home
It shows for every task they test closed models do the best. The closest and open model gets is Minmax 2.7 on issue resolution where it's ~1% worse than the leaders.
That matches my experience - fine for small problems, but well behind has the task gets bigger.
When I argue this, my point is that FOSS shouldn't target the desktop with open weights - it should target H200s. Really big parameter models with big VRAM requirements.
Those can always be distilled down, but you can't really go the other way.
Subsidizing is the opposite of competing. It's literally the practice of underpricing your product to box out competition. If everyone was competing on a level playing field they would all price their products above cost.
All these tech oligarch asshat companies need to be regulated to hell and back.
For many things now you need to go local and in the future if you want any privacy you'll need to go local.
Big players operating at loss to distort the market is not a good thing overall.
It's not the smaller players spending billions on training data.
- Claude: Good for ~20 minutes of work once every 4 hours
- Codex: Good for however long I want to use it.
- sysadmin tasks for my home server which runs home assistant, plex, and minecraft servers. Being able to tell it "Set up a minecraft fabric server with this list of mods" is pretty nice, and it's fairly competent at putting together home assistant dashboards and automations (make sure you have backups of anything it's allowed to touch, though--it may delete stuff without warning).
- Several small web apps primarily for my own use.
- Currently working on an opinionated desktop writing app for my own use.
The Anthropic 20 USD plan would more or less be a non-starter for agentic development, at least for the projects that I work on, even while only working on a single codebase or task at a time (I usually do 1-3 at a time).
I would be absolutely bankrupt if I had to pay per-token. That said, I do mostly just throw Opus at everything (though it sometimes picks Sonnet/Haiku for sub-agents for specific tasks, which is okay), so probably not a 100% optional approach, but I've wasted too much time and effort in the past on sub-optimal (non-SOTA) models anyways. I wonder which is closer to the actual cost and how much subsidizing there is going on.
But Opus is both smarter and faster than GPT, so I can get a lot more done during the Claude limits.
For me $20 a month is more than I want to spend I just use the free tiers. If I use AI in an app or site I use older models mostly chatgpt3.5. The challenge is more fun and it means I can do more like, make more api calls - 100x more.
A couple weeks ago I'd get roughly 2~3 hours. And a month before that I couldn't break the 5-hour limit.
Which makes it even more of a shame that Sam Altman is such a psychopathic jackass.
This is normal behavior and not a cause for such a hyperbolic response.
Pricing your product unsustainably vs a competitor to gain market share is regarded as "bad competition" and has historically been seen as anticompetitive.
It does not benefit the consumer in the long run, because the goal is to use your increased funding or cash reserve to wipe your competition out of the market, decreasing competition in the long term.
Then, once your competition is gone, and you've entrenched yourself, you do a rug pull.
We need to force them back into being providers of commodity services and hit this assumption they can mold things in real time on the head.
> To help you go further with Codex, we’re introducing a new €114 Pro tier designed for longer, high-intensity sessions.
> At launch, this new tier includes a limited-time Codex usage boost, with up to 10x more Codex usage than Plus (typically 5x).
> As the Codex promotion on Plus winds down today, we’re rebalancing Plus usage to support more sessions across the week, rather than longer high-intensity sessions on a single day.
It's because they don't support OpenCode.
When OpenAI snatched those contracts, it made me think no worse of OpenAI. The surveillance was already factored into how I saw them (both).
They're doing a slow rollout