I turned off Anthropic properly and switched all of that over to OpenAI yesterday. (I use other models for other things too, especially DeepSeek in Pi).
Honestly aside from the voice it uses you wouldn't notice a difference. Switching costs are low, vote with your wallet.
> I turned off Anthropic properly and switched all of that over to OpenAI yesterday.
Same, just a while longer ago.
I much prefer how OpenAI models write to Anthropic's, will probably revisit Anthropic in a generation or two. Context size is more limited, but no critical forgetfulness due to compaction so far, though I also like having plan files around both for future reference and improving chances of success at long form work.
Also tried out Kimi K3, was nice but slow (and apparently routed some requests to Claude anyways), GLM 5.3 was faster and still pretty good but the token allowances were kinda limited.
I would like to have alternative to chat - model and provider agnostic (BYOK), but with history, project, maybe memory, with good search and quality tools.
I know openwebui and i dont want to host it.
codex (their app) is pretty good and lots of banked resets, luna is cost effective and Astra seems better than Fable for many tasks. Most important one is less refusals and I can use it the way I want without the fear of getting banned. I do like Claude Code a lot when it comes to pure coding use cases but the work often touches outside code and I don't want to keep switching
> I do like Claude Code a lot when it comes to pure coding use cases
The harness is great, but opus is such an arrogant little prick that spews out unintelligible word salad. Opus 5 is so bad at communication it amazes me that somebody green-lit it. It's absolutely awful.
The fact that this isn't an acknowledged regression (and Fable 5.1 isn't much better) leads me to believe that people at Anthropic actually like Opus 5's output.
This is why I'm hesitant to buy Google AI again. I don't want to risk some npm install compromising my Google account which also happens to do AI coding.
I think this is a move to get people off the subscription and move to API. The weekly usage is still awful altough it seems they're trying to fix it but I'm not hopeful.
I wonder if these benchmarks swap words, meaning and more because you might as well be benchmaxxing for specific words. I notice a lot of recurring just structural sentences coming back in smaller LLM models where they're fit for a specific task which is fine because most of the work we do is repetitive and there are patterns to learn but they should be word agnostic which I wonder if LLM can really fix.
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