> It's a damn good model. Not quite as "smart" as Fable, but it is incredibly capable. Fixed all the problems I had with GPT-5.5.
> It is incredibly determined. Will run for a day without even using a /goal. It understands subagents incredibly well and is great at orchestrating. It's super pleasant in use cases like OpenClaw and Hermes Agent. It knows iOS dev incredibly well.
> It has rough edges too, but FAR fewer than 5.5 did.
> For many things, gpt-5.6-sol will become my obvious defaults.
> It is better about [following instructions] than 5.5 was. Understands intent well and hammers until it gets there. Sometimes a bit too hard.
Also[^1]:
> gpt-5.6-sol is world leading in computer use. It made me use it 100x more. When we lost access to 5.6, I quickly started to go insane without it
[^0]: https://nitter.net/theo/status/2074708892341481755 [^1]: https://nitter.net/theo/status/2074720467395756499
Every time I've ever seen one of his videos it's pretty clear he has very little understanding of development or engineering. I first became aware of him from his early "unit tests are a waste of time" stuff, and it seems his skillset is building a personal brand. Fair play, he's clearly talented at that, but that doesn't make his opinion on anything else worthwhile.
I cannot prove it but I have a feeling that you may be conflating "he clearly has different opinions on things I consider non-negotiable" to "he doesn't know what he's talking about".
I also watched a lot of his videos. I wildly disagree with him a lot of times, but he has his reasoning, and I can see (and verify!) that those ideas are coming from an engineering perspective.
THIS IS BECAUSE GPT-5.6 SOL IS... just a more posttrained version of GPT-5.5, not a brand new bigger model than GPT-5.5. It's not like how Mythos is bigger than Opus.
OpenAI switching to Sol/Terra/Luna renaming is just a way to rip off people and charge more money for the same sized model.
GPT-5.6 --------> GPT-5.6 Sol
GPT-5.6-mini ---> GPT-5.6 Terra
GPT-5.6-nano ---> GPT-5.6 Luna
Except OpenAI is about to charge way more money for GPT-5.6 Sol and GPT-5.6 Terra, than if they named it GPT-5.6 and GPT-5.6-mini.
So, if they improved a lot in those areas, then GPT-5.6 could become a lot more useful compared to GPT-5.5 even though it might score lower in many benchmarks. It's possible but unlikely since their approach was mostly brute force in the past.
Excuse me, but what are you on about?
Unless I'm mistaken, they have literally(1) stated that it will cost $5 per 1M tokens in, and $30 for 1M output tokens. The same as GPT-5.5.
(A little toning down of the goblin fetish would be nice too, haha.)
https://x.com/theo/status/2074708892341481755
5.6 sol seems to hit a lot of the gaps with 5.5
sucks its not "mythos" but i will take it
If there’s anything I learned over the past 12-18 months is that this is a recipe for disaster, except for throwaway stuff.
I thought most senior engineers settled on the fact that steering a model yields much better results?
OpenAI switching to the Sol/Terra/Luna naming is just a way to rip off people and charge more money for the same sized model.
GPT-5.6 --------> GPT-5.6 Sol
GPT-5.6-mini ---> GPT-5.6 Terra
GPT-5.6-nano ---> GPT-5.6 Luna
Except OpenAI is about to charge way more money for GPT-5.6 Sol and GPT-5.6 Terra, than if they named it GPT-5.6 and GPT-5.6-mini.
Two important things to note, if you want to verify what I say/correct me:
GPT-5.6 Terra actually scores worse than GPT-5.5 on many benchmarks. It's not GPT-5.5 trained with more compute; it's basically GPT-5.6-mini that's been distilled from GPT-5.6 full size. Remember, GPT-5.4-mini had almost the same benchmarks as GPT-5.2 after all.
Opus 4.8 runs at ~90 tokens per second. Fable 5 runs at ~40 tokens per second on from Anthropic, because it's a bigger/slower model. A few days after the release, when the dust dies down, look at how many tokens/second GPT-5.6 Sol is running at. I will bet it's the about same as GPT-5.5, and not half the speed. (OpenAI is not incentivized to slow down the model for paying customers). But the model tokens/sec will be a big clue- if OpenAI is charging more money for the same sized model or not.
I also flip between the models due to quota, TUI enhancements, model updates and service availability.
To handle this, I built a thing that normalizes your transcripts between Claude Code and Codex into a shared DB, then a CLI and skill.
It has made it so it doesn't matter what I built where (or when) I just refer to the work and drop in a /total-recall (or $total-recall on codex) and the agent brings it into the current convo.
I realize there are a lot of ~memory tools out there, but I think particular my approach and product behavior is unique.
If you're open to giving it a try, I'd appreciate any feedback: https://contextify.sh recent show hn: https://news.ycombinator.com/item?id=48777790
Edit: I guess the real answer is that I don't want multiple subscriptions. I use one for a month, and then decide if I switch to the other.
e.g., it still doesn't have /revise or /undo!
Using cheaper models and using your skills and expertise from the pre-AI era can get you working just as fast. You've gotta be more specific about the work you need doing. It's less "vibes" based, but they're still effective.
Also, Chinese models absolutely are taking off. I used Claude and GPT at work, and then I tried using some Chinese models for personal projects. I am 100% convinced they're like 90% as good for 10% of the cost. But you've basically gotta be a good developer first and know what you want and know when it's giving you shit.
If OpenAI can launch a Fable tier model that's actually usable on a subscription, then Anthropic is just going to lose, and badly.
I'm guessing this works better because it can always go back and re-analyze the saved context.
Why do they store an encrypted reasoning payload in the session file and pass it to the API? Just a ruse? Reasoning isn’t even that many tokens, you think they’d degrade their model quality like that?
Reasoning messages would be lost immediately after a single tool call, unless you mean they sometimes go back and strip the reasoning channel retroactively, but that would increase costs via cache invalidation. I just don’t see any way it would make sense for them to do.
And wouldn’t this be noticeable by reasoning tokens not being accounted for in the context window usage?
Were you able to try Sol Ultra?
So claude: 10 paragraphs of prose
codex: 1 paragraph of jargon over jargon.
UX is nicer where the agent is somehow "separated" from execution.
None of these were Theo's take. He was pushing the idea that unit tests in general were a waste of time because you could be shipping new features instead.
https://www.youtube.com/watch?v=pvBHyip4peo for an example of this. The nicest possible interpretation on this is that he's deliberately saying something he knows is wrong to attract attention.
Our docs show a diagram here:
https://developers.openai.com/api/docs/guides/reasoning
> Input and output tokens from each step are carried over, while reasoning tokens are discarded.
Keeping reasoning tokens around is better for caching and for remembering past insights, so you might reasonably wonder why we designed it this way. The main benefit of dropping reasoning tokens is that you can fit a lot more work inside the model's context window before you're forced into a slow and lossy compaction step. This was a larger consideration with our earlier reasoning models that had shorter context windows (~200k), longer thinking times (up to ~100k per message), and poor compaction. However, now that we've shipped longer context windows, we've trained our models think much more efficiently, and we've made compaction way better than it used to be, the balance of factors is changing. Tune in Thursday!
In my experience even Fable still requires guidance (although the options it provides are generally better).
- alpha testers will start getting access now
- everyone will get access Thursday (barring banned countries / individuals)
Historically, some companies and individuals have gotten alpha access before public launches, to give feedback and adapt their products to the new models. With GPT-5.6, some folks had alpha access, but this was taken away while the model was being evaluated and approved. Now, alpha access will be enabled for some partner companies in the next two days before our wider launch.
I work at OpenAI.