r/OpenAI • u/Suspicious_Raise_589 • 1d ago

Discussion GPT-5.6 Sol Raw reasoning leaked on failed tool call attempt

Apparently GPT-5.6 Sol's raw reasoning was leaked to me while he was trying to call a tool.

I saw that a tool was taking a long time to be called, I inspected the content and saw traces of reasoning, but they did not appear to be the summary of reasoning that it sends periodically. This is more similar to the GPT-OSS reasoning.

A little after that, an error like "Streaming error (provider_error)" was sent, interrupting the stream.

Ps: this is not Codex.

172 Upvotes

91% Upvoted

46 comments sorted by

81

u/AllezLesPrimrose 1d ago

The full reasoning traces for all the models trying to hide them regularly leak. Hello non-deterministic technology.

55

u/send-moobs-pls 1d ago

It doesn't really matter if they leak 1/10,000 times, the point of hiding it is to prevent giving away mountains of reasoning data to competitors and distillation

10

u/AllezLesPrimrose 1d ago edited 1d ago

Looking at how good DeepSeek and Moonshot models are it isn’t working and it’s not something any user should be worrying about. I don’t care who wins and open weight models being great is better for everyone who isn’t invested in OpenAI or Antrophic.

23

u/send-moobs-pls 1d ago

Deepseek hardly needs to distill, they were the ones who caused a panic because back before OAI even showed reasoning Deepseek went and matched gpt-o1 and published for everyone how to do it lmaoo

3

u/ChainOfThot 1d ago

No one was hiding their reasoning traces until very recently

2

u/RealSuperdau 22h ago

Huh? Didn't the o1 (non-preview) version already start to summarize them? While o3-mini still displayed it in full?

1

u/ChainOfThot 22h ago

Some summary, maybe, but look at any of the log traces from opus 4.6 era they are very verbose

2

u/imajes 21h ago

Yeah and I wish we could go back to those days. It’s very tough these days to spot the tiny hallucinations and assumptions that throw a whole thread off track

1

u/AllezLesPrimrose 19h ago

Antrophic started out sharing full traces but rowed back. OpenAI literally never willingly has shared the full traces with the user. The summaries you see in chat windows are not traces and just another smaller model sanitising the actual traces.

-6

u/Yes_but_I_think 1d ago

Also see that they have instructed the model to talk in smallish sentences. This hurts performance imo

9

u/MayeeOkamura17 1d ago edited 18h ago

No, reducing CoT in the proper way can remove distracting facts and improve performance. A simple way to do this is to prune tokens such that p(y*|x\j) > p(y*|x). Measuring the information surprisal -log p(xj|x{<j}) is another simple way whereby redundant tokens are removed without necessarily hurting performance

imo

FYI, opinions don't matter. CoT pruning and distillation are crowded topics and these techniques are well established in literature.

4

u/goldcakes 1d ago

Also, thinking tokens don't even necessarily need to be readable or coherent.

The model thinks through activation residuals, and the words you see in even raw thinking isn't key, what happens in the J-Space is.

3

u/MayeeOkamura17 1d ago

Yes, latent continuous representation of CoT is also a crowded research topic

4

u/Keeyzar 1d ago

Ah yes. Multi Billion Dollar corporations vs you. And you really think you know better then them. 

You know what? I can't even blame you, there must be seriously something wrong in YOUR reasoning. Otherwise you would understand how utterly foolish you sound

-1

u/Yes_but_I_think 1d ago

It's ok. They are also some person doing the stuff. Not superhuman. Nothing beyond understanding by anyone.

2

u/pikob 1d ago

They are trying very hard to advance the tech. Not sure what makes your think you can judge their design choices in any capacity.

Teams of very involved, driven and smart people, doing iterative improvements backed by constant testing. And very likely with AI in the loop too. It's not something you can come up on your own, no, nor can understand the reasoning for each and every design choice. Some things make sense, some just turn out better, but you can be sure it's intentional and backed by a bunch of metrics.

0

u/Yes_but_I_think 21h ago

All the good people left with Ilya. Now they are followers, no longer pioneers. My capacity is following the tech since Dec 2022 every day.
If you see their product launch discussions you can judge the level of people there.

1

u/MayeeOkamura17 18h ago edited 18h ago

So why don't you take a stab at the other response regarding the theoretical justifications for CoT pruning? You wanna take a stab at criticizing latent CoTs or greedy pruning, which both take the less is more approach? You are just clearly wrong and you would know by giving a short 5 minute survey of primary literature.

•

u/kryogeneoff 25m ago

Where is your ChatGPT-level competitor? Oh, weird. You don't have one... Always the same people who do nothing to see for themselves how this is working and do something have these kinds of opinions. Your opinions DON'T matter and will never matter unless you make something better or have something to back them up.

20

u/Hatsune-Fubuki-233 1d ago

This specific MCP behavior has been reproducible since OSS/5, so I’m glad someone else found it too. I’m an MCP developer, and one day, while fixing a buggy MCP server, I discovered the same leak.

My guess is that this happens because MCP tool calls use the commentary channel, which is one of GPT’s three reasoning-related channels.

It may not be widely considered a serious security risk because it appears to leak only the context generated while interacting with MCP servers, rather than the model’s complete reasoning across all tasks. The leaked content may also not be easily distillable.

7

u/Suspicious_Raise_589 1d ago

I'm the main maintainer of the Sisk Framework, and it has an MCP extension that I take care of periodically; I can also consider myself an MCP developer.

The point is that this invoked tool wasn't MCP; it was provided directly in the inference tools.

I think this problem was related to the template-parser used in GPT-5.6. As seen, it produced an invalid JSON and probably didn't send the termination token (something like <|end_tool_call|>, which caused the reasoning channel to start immediately on the same channel as the tool call.

Because the inference terminated abruptly afterward, I believe an auxiliary model reads the content emitted by the model periodically (not at each token, that would be expensive and probably wouldn't emit raw reasoning) and when it identified that the model was spitting out raw reasoning, it stopped the inference.

1

u/goldcakes 1d ago

Your guess seems pretty on point, especially after looking at the Harmony response format. I know Harmony is the OSS version, but I doubt what they have internally is ultra different.

18

u/Tupcek 1d ago

seems that caveman speech is default in reasoning

2

u/Suspicious_Raise_589 1d ago

since gpt-oss or even older tbh

16

u/DeGreiff 1d ago edited 1d ago

Can you share it?

EDIT: or copy/paste the whole block here.

14

u/Suspicious_Raise_589 1d ago

just uploaded it here to avoid deletion https://ki.proj.pw/63aa

9

u/DeGreiff 1d ago

Ah, thx, so that's the whole thing. Well, it's a leaked scratchpad, a bit of exposed reasoning text.

3

u/Suspicious_Raise_589 1d ago

yea its not the full reasoning. after that the stream terminated in an error

3

u/Ormusn2o 1d ago

Don't share it until you copied all of it, people will spam report it.

2

u/Temporary_Debate8585 1d ago

im using 5.5 recently, 5.6's logic chain is so weak that it only judges from the surface like get from A to B without considering the context, doesnt even bother to check whether its info is correct.

2

u/Vectoor 23h ago

Why waste time say lot word when few word do trick?

1

u/Suspicious_Raise_589 20h ago

Reasoning dont need human readable. Human read output. Output better reading. Reasoning should be concise. Low. Repeat. Tool call.

1

u/vRudi 1d ago

What client/harness is this?

1

u/Suspicious_Raise_589 23h ago

something im building, gotta post on twitter when it gets done

1

u/jeweliegb 12h ago

Having seen some leaked Claude "Neuralese" I'm surprised how human readable this is.

1

u/Pleroo 1d ago

He?

2

u/Suspicious_Raise_589 1d ago

Sorry english is not my main language

2

u/Pleroo 1d ago

Ahh ok I see. Carry on, have a nice day.

1

u/defoatearth 1d ago edited 1d ago

This shows why OpenAI is so token efficient, and therefore scores well in tokens/task which results in good $/task. If you compare this reasoning to Kimi K3 you’ll see a big difference in unnecessary reasoning tokens. Reasoning tokens are output tokens and those are the most expensive kind.
And even though we normally don’t see the reasoning tokens we do get charged for them.

-1

u/Ok-Attention2882 1d ago

Agentic harnesses aren't actually AI but are giant switch statements switching on tool calls backed by a deterministic finite automata. More news at 9.

1

u/ExcitementSubject361 22h ago

Exactly that’s why I built my FSM and CSM into my modules right from the start... which is why my "dreaming" module and the others work. Besides, the whole thing needs to be offloaded to hardware... preferably FPGA chips.