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by fnordpiglet 20 days ago
Hmm ok. The fact 5.6 Sol performs around Fable level and is included without mega token spend in the subscriptions means I’ve promoted codex to my primary harness and model. The latest release of the CLI, app, and desktop fills a lot of the gaps.

Anthropic painted itself into a corner with fable at many turns and this latest twist is one of the more interesting. Either fable is too expensive to run at scale, or they’re trying to incentivize mega spend on tokens, or whatever - but them locking the frontier model away for the few enterprises willing to spend top dollar while codex is including frontier in the subscription (and I’ve found it also is both less token hungry and the limits are much higher for codex) has finally made me put Claude aside and use it as my backup for very specific tasks, where codex has filled that spot for a long time now.

50% more weekly limit, but no fable. Ok. I might have a refactoring job somewhere for you Claude for those extra tokens.

2 comments

Exactly. We are all on Claude where I work but as soon as the costs rise we are migrating. Changing to a new coding agent stack feels like it will be about as much effort as migrating to a new keyboard. Gross or painful for about a week or two.
Which is why these companies must be overvalued. This is the definition of a commodity. We have no loyalty to any vendor or model, it's just about capability, price and performance and there can only be so many more increments in capability before these models are good enough that it doesn't matter which you use for 99.9 pct of tasks and the frontier moves on to robotics or the next hard domain (which OpenAI / Anthropic may not lead). I predict that in a year I'll be using whatever the latest version of Gemini flash is (because it's fast, on my mobile and multimodal), and some small cheap open SWE expert model for dev work.
Don't get me wrong, I love Claude code and there is some loyalty I feel. But just can't justify staying if costs 2x.
> This is the definition of a commodity

Not really. It’s the definition of a tight market with two leaders.

When folks start running various rando open-source models locally instead of well-recognized brands, then we will have evidence of fungibility and thus commoditization.

I'd say for some sectors and users, we're already seeing that. After GLM-5.2's release there were quite a few stories about it picking up use.

Then looking at Openrouter's stats we can see heavy use of non Anthropic/OpenAI models https://openrouter.ai/rankings#top-models

I'm not sure I'd call them rando, but Deepseek/Qwen/GLM all have decent models that will work fine for some use cases at much lower costs that the SOTA models from Anthropic/OpenAI.

Exactly. As soon as business works out that there are open models that can achieve parity at a fraction of the cost, they will switch model. They have to. Business exists to make money, and if they can do the same thing at lower cost, they will.
I recently swapped to Codex and its pretty great after a day or so of migrating configs and wrangling Codex's bubblewrap and finetuning the auto mode classifier prompt.

Claude is now mostly demoted to Claude Design.

I liked the fact that ChatGPT web chat usage is separate from Codex usage.

I'd say 5.6 Sol performs between opus and fable, but not yet fable.

Just that given its cost efficiency, claude subscription isn't attractive at all when fable is removed.

Agreed. It’s also a lot better at following instructions. If anything codex can get caught into an overly literal adherence to instruction while Claude you can barely trust it to sit still for 5 minutes. Tell Claude to use an MCP for a task, 30% chance it’ll do it. Provide it skills, 10% chance it’ll use them when appropriate. Codex is almost the mirror of that. It’ll almost always use the MCP and recall the skills.

The challenge I think for codex is the restriction on context size and the constantly rolling compactions. They are less aggressive or disruptive but it is still annoying you can’t force a 1mm context window on a 1mm context window model.

But it’s recall beyond compaction boundaries is much better than Claude code. The impact of compaction is much less noticeable.

Performance on task work is between fable and opus, but the marginal utility between that gap is not enough to pay extra.