alt Hacker NewsGPT-5.6
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Based on the Intelligence vs. Cost graph, not clear to me why anyone would use Terra? Luna looks quite interesting though, happy to see OpenAI still serving the more budget-oriented side of the market (seems like Anthropic and Google have lost interest there).
Will this run on Cerebas? I'm really looking forward to that.
Zero information on the knowledge cutoff. The model itself responds it's June 2024 which is weird given that GPT-5.5 has knowledge cutoff at August 2025.
I think 5.6 Sol is only as good as 5.5 or Opus 4.8 in terms of getting its given work done. It just has an uncanny ability to pickup more work that it can tackle next that the older models lack, or have not been trained to do before. Where folks are seeing a difference between working with Fable or 5.6 I think also boils down to this phase shift.
Dirac (https://github.com/dirac-run/dirac, https://dirac.run/) now supports gpt-5.6. This thing does now seem to be on the chatGPT/codex accounts yet.
UPDATE: it is now available in chatGPT account also, they rolled it out
Not sure what everyone's experience is but I find 5.6 Sol to be a great liar. Reported success on a half done job and left things in a broken state after having quite a few back & forth followups on the initial prompt to clarify the plan. Didn't experience this with 5.5. Opus 4.7 and below sometimes did it but they fixed it in Opus 4.8. So, overall, the initial experience has made me think that this model will be a lot more stressful to work with just because the level of trust that it actually completes the task is now much much lower.
I find that 5.5 gives me far fewer refusals than Anthropic models for security and reverse engineering work. I hope the same is true for 5.6.
Logged into the OpenAI platform this morning and had to double check they hadn't pivoted into a crypto company with these new names
On the tiny voids demo: does your Firefox js thread lock up as well, when you try to interact with it?
Oh man, I love capitalism spoiling us here. I was just enjoying my extra Fable credits, now I'll switch to using 5.6 this weekend. I was planning to ration my Anthropic credits, I guess now I do not have to. And I was half wondering if exactly this would happen: right when Fable usage credits were starting to kick in for people, OAI swoops in and takes the puck. As much the AI craze is crazy, this play by play part is pretty fun.
There is an issue on the page that causes the benchmark tables to get cut off. If you highlight and drag right you can see a few more models like Gemini and Claude Opus. It's also interesting that they introduced explicit caching, which is something that only Anthropic had for a long time.
I am seeing some bugginess in testing:
Parameter: reasoning_effort
Function tools with reasoning_effort are not supported for gpt-5.6-sol in /v1/chat/completions.
To use function tools, use /v1/responses or set reasoning_effort to 'none'.'
I hope we aren't trying to push customers off the chat completion endpoint... Responses endpoint looks great on paper, but the business wants more visibility and control over the reasoning process than this product currently offers.
Edit: This is broken in my VS copilot setup too.
> Your subscription to Claude Max has been successfully canceled.
Switching next month. Looking forward to working with Sol.
> Instead of requiring developers to script every step or passing every tool response back through the model, Programmatic Tool Calling in the Responses API can filter large amounts of intermediate data, retain only what matters, and adapt its workflow along the way.
this seems very interesting
The claims are pretty bold. I think 5.6 may exceed Fable.
I guess Plus accounts don't get access to Sol? Or is it because I am in Europe?
Looks like a great set of models, but there are about 20 different thinking/model levels here in this family and they are very complex to pick the right one for the task
E.g. for GeneBench Pro, it looks like you would always use GPT-5.6 Sol over Terra/Luna, its pareto optimal.
For Agents Last Exam, you would maybe want Luna, then Terra, then Luna, then Sol as you increasingly budget for tasks.
I feel that there may need to be a new auto mode in many of these cases. It selects the best model and thinking given a particular problem.
Feels like it's going to have to go that way eventually, because here we have about 20 different model and thinking levels you could use, and they're not obvious which ones are right for the given use case.
I wish model launches were like proper product releases
it's impossible to _try_ it out on release!
it's not on their codex subscription, or the web/mobile chatgpt interfaces, or aws bedrock, etc. I just cant find a working endpoint with the latest model after they announce
One of my best use cases for the short duration I have fable is to use it to create the plan and acceptance test files then use GPT 5.5 Pro to do an adversarial review on the plan then feed that feedback into fable to fix the plan.
I've played around GPT 5.6 sol high at both work and home.
At work, it was able to one shot a dashboard. Of course, my prompts are vague as I'm not exactly sure what I want yet, but it did a better job than I could do as a backend dev forced to work on frontend sometimes.
Usage is also great, it just feels so much more efficient than older models in terms of thinking and time. Cost is barely better though.
It can burn a million tokens in less than a minute, at least at launch where there's likely less load on the servers.
At home, it feels like I'm fighting the AI less while letting it refactor code. I'm glad that I left this 12,000 line vibe coded port of a hand written codebase to future models to refactor. It feels like the model has better judgement than old models that would destroy your codebase so long as it meant accomplishing your prompt.
I'm almost disappointed that it's this good.
Looks like I have access to gpt-5.6-terra and luna. How does one decide between gpt-5.5 and gpt-5.6-terra? Pricing is similar, but it's hard to tell if it's better..
We have an official pelican on a bicycle from the OpenAI livestream:
So with this release do they kill the 5.5-Pro model with super long thinking and reasoning? 5.6-Sol-Ultra is not the equivalent, right?
Anybody have an idea of what the flops per token generated is on a SOTA model like current GPT/OPUS? Is it basically the parameter count? So something like GLM-5.2 is, at a minimum, ~744 GFLOPs per token generated?
Am I way off base? Seems astronomical.
I use both Claude and Codex, but mostly Claude for planning and coding, and Codex to review Claude’s work.
I follow a sort of waterfall workflow which is verbose but fully transparent.
Anthropic’s $100 subscription works fine for me, but whatever subscription my company has with OpenAI reaches the 5hr limit ridiculously quickly.
Where is Gemini in all this? Lately it's not even been in the running. Sir Demis asleep at the wheel? Or Google too scared to release a SOTA model?
Or ... maybe Gemini 4 is too good and the NSA is using it to break into systems worldwide ...?
GPT-5.6 Sol, Terra, and Luna. at this rate GPT-6 will be named after a parking lot and GPT-7 after whatever Elon names his next kid.
On top of GPT 5.6 Sol they added a Tamagotchi / Clippy mascotte https://x.com/giorgio_zampa/status/2075319657997750495?s=20
It scores high on BenchCAD, that's interesting to see, I was wondering about how each model could handle this. Seems like they trained it on programmatic CAD specifically.
devops monster! crazy how intelligently it debugs/solves any devops problem I could throw at it!
I never have have the issues most people talk about ... I feel like most were never Devs before ai and don't know what they actually need done when prompting. that on top of not utilizing good tools such as a codebase indexer, lsp and a project scaffold.
If it's not dangerous enough to be classified as WMD by USG, who's interested.
The cost & output token charts are useful but I wish I could view them more like a 3D surface. Like the CS:APP memory mountain charts.
I wonder how long model size and effort will be a few discrete points instead of continuous.
it seems terra is pretty much useless, you either want luna max for everyday coding (cheaper and same perf as 5.5 high), or sol xhigh/max for demanding tasks
GPT‑5.6 system card https://deploymentsafety.openai.com/gpt-5-6/gpt-5-6.pdf
Maybe it’s a bug but on iOS individual paid Pro account - I can no longer see which model is being used nor select which model I want.
For context, I have access to MS Copilot through my workplace. To see what it looks like, I have tried to login through https://copilot.microsoft.com/ , where I was informed that my account, although recognised, is not yet supported. However, I can get more or less the same chat window, with access to all the data, through https://m365.cloud.microsoft/ A redirect could have been useful.
Trying to play those games has really bad impact on PC performance
"GPT‑5.6 is available starting today across ChatGPT, Codex, and the OpenAI API. The rollout is starting globally now and will continue gradually toward full availability over the next 24 hours."
After some time with it...
It has a tendency to do things without asking, a trait I'd associated more with the Claude Opus & Sonnet models than with Codex & GPT in the past. Specifically I've seen it go and update e.g. README.md files filling it with recenty-biased gibberish that means nothing to the user (e.g. very specific technical notes related to what it was currently working on) or staging and adding design/spec documents that were meant to just be working documents. In general it tends to behave more aggressively with git, if you let it get its hands on it. It has stronger "opinions" on that stuff, that don't always agree with me.
I'm going to have to update my prompts, I think. But I'm not used to this kind of thing in Codex, which in the past has been much more explicit and cautious, and one of the reasons I've preferred it over Claude.
It is very "smart." It also has a tendency to yak-shave things. Producing huge volumes of correctness and regression tests and nitting over e.g. very minor variances.
One thing that is "entertaining" is letting two separate instances review each other's code. They will endlessly find things to nit at.
This marketing video on the page is nice!! can't wait for the hardware to get cheaper to live the AI life i wanna live.
I hope it isnt like Opus eating so many tokens and taking so much time
Really wanna see it in DeepSWE benchmark
it seems like 5.6 SOL is better at almost everything than Mythos except Coding Benchmarks (except TerminalBench)? anyone knows why Mythos scores so high on SWEBench are they cheating or are they just optimised better for coding?
I wish they had kept their previous sensible naming convention instead of this celestial Sol, Terra, and Luna mumbo-jumbo
we probably need to use gpt sol max to decide which gpt flavor and effort we need to use per task.
I would be really interested in real life throughput. For an agentic chat situation, we are still on 5.4 - not because of the cost, but it's simply much faster than 5.5 with comparable results. Also we are using gpt-5.4-mini a lot for quick summaries, tldrs etc. In an ideal world we would upgrade 5.4 to 5.6 terra and 5.4 mini to 5.4 luna. But does somebody already have some measurements at least in terms of speed?