Anthropic is losing bigtime against Open AI in coding space. I was using Claude code upto last march. Not an enterprise customer, but a responsible AI user where i don't over spend and use basic plan to manage repository with 400Kloc all together. We sell to local government and a team of 3. Claude code was super slow, never able to fix issues properly.(Despite with proper test cases, observability, documentation and layered architecture). After moving to codex, life has been much easy and free form usage anxiety. Now managing entire things with 2 codex plus account per team member. Its high time anthropic should stop scare mongering and build efficient models. Everyone doesn't need Fable. People need models that solve problems efficiently.
I've found Opus 4.8 pretty amazing, and Codex a bit meh. YMMV?
I just downloaded and paid for Codex this week because I want to stay on top of the AI tools and understand their capabilities. I've had some good results using 5.6 Sol, although it tends to never want to write any comments (despite modifying the project rules to tell it it MUST), and also occasionally just does a bit of thinking and stops. It'll say "Working through the remaining work" and just ends the chat until I tell it "continue" or something.
This is very anecdotal evidence but I have to rant about it... I tried 5.6 Terra (high) earlier today to fix a bug with a slow page. It just... removed the part of the page that was slow, and made it a client side request (still slow, but not blocking SSR I guess). I tried with Sonnet 5 and it correctly found the issue where an unhandled case was continuing to retry and failing. I am always telling people how the frontier models are SO much more capable than what they may think but this one thing today had me scratching my head at why it would ever do that. It was the first time I experienced the "great, I removed the failing test case" kind of issue.
I got the complete opposite of what you get, sol ultra literally vibed the entire system out for me from one plan mode approval.
I think the comment you're replying to is talking about cost and speed, and Opus 4.8 xhigh is pretty expensive and pretty slow. I work around the slowness by having multiple auto mode sessions going in parallel (review this, investigate that, plan this, etc.; and yes, I use a VM that can't touch prod for auto-mode work), and work around the cost by my employer pays for it and everyone else I work with uses more AI than I do :)
I really really like Fable for software engineering cases; add an alert and write a runbook, go pull metrics for this incident, write me a TUI that does blank, etc. It is astoundingly good and I am very picky. It costs A LOT of money though. I am not sure how I get away with my Fable usage.
There is one thing that stay apart, I can use luna high with pretty less cost and do a comprehensive audit using sol high on every push from github.
My only issue with Codex (Sol 5.6) is that it sometimes finds tasks on its own to solve that are definitely out of scope. like it’s always aiming for the 1.0 release when we’re still on 0.1.0a
I think it depends on the problem space, and to a large extent the languages used. I have had the opposite experience with GPT.
I have found GPT to be pretty awful at writing Elixir, and dealing with more open ended tasks. Opus is (for the moment) better at writing Elixir, and Fable is much better than either at actually grokking a problem space. I had switched to GPT for about six weeks and eventually stopped using it altogether after it relentlessly gaslight me. Those six weeks using it were essentially completely wasted work.
Right now I’ve moved to a mix of Opus/Fable and Deepseek Pro. Deepseek is far and away the most cost effective, fast, and quite good for 90% of implementation work. Deepseek really only falls apart (in Elixir) when it tries to use runtime features at compile time; which, for the initial lift of a project I have was a bit painful. Fable was able to pretty quickly get things sorted and now things are progressing nicely.
With all that said, I think the various models have unique strengths that are sometime hard to uncover. I also don’t see a world, at least in the near future, where I’ll only use one model. I’m happy Anthropic continues to push the frontier forward. I’m more than happy to trade “efficiency” for quality when I need to.