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I believe that most reasoning models actually think in their own "language" which is not really understandable by humans. The thinking traces that are shown in

I believe that most reasoning models actually think in their own "language" which is not really understandable by humans. The thinking traces that are shown in the UI are actually summaries generated by a smaller model in plain english (or user language). Sometimes this leaks through and you see some chinese/japanese characters in e.g. Claude's reasoning.

seydor 4mo ago
> summaries generated Or hallucinated
dryarzeg 4mo ago
As far as I'm aware, it's not true for models like DeepSeek or other Chinese open-weight models (at least those that I have seen); their reasoning traces are fully composed from some human language, be it English, Chinese or another one; by the way, most of them can adapt their reasoning based on user language, for example, if user speaks English the reasoning more likely will be in English. I think that for DeepSeek problem (thinking and replying in Chinese) everything is kinda simpler: in their official chat, they're probably using some kind of system prompt which is (probably) written in Chinese, so that's why model may prefer Chinese in it's output.
- calgoo 4mo ago
  I have seen mixed language thinking from claude when i speak to it in english but we are discussing a product thats in spanish or searching amazon spain.
kgeist 4mo ago
Summaries by different smaller models are usually made by closed proprietary models like Claude as a way to combat the distillation of real reasoning traces by competitors. Open weight models show the real reasoning traces. Reasoning traces operate in the same space as the non-reasoning output. It's all just one large text for an LLM. Internally, reasoning is just ordinary chat completion between <think></think> tags.
ForceBru 4mo ago
Wait, this isn't real, is it? Is there actually an intermediate model that translates DeepSeek's thinking from its "alien language" into human languages? That's not actually the case, right? I thought "thinking" is literally the model generating additional text in a human language that shows its "thought process". It's added to the model's context, which helps it reason better because it now has this self-generated context. The "their own language" idea seems to come from some recent science fiction where LLMs develop their alien language and take over the world by 2037 or something.
- Gracana 4mo ago
  You're right, it's just additional text that allows it to do thinking / reasoning-like behavior. The big proprietary models hide the real output from the user and instead provide a friendly abridged version, but that's just to protect their secret sauce from distillation.
- mcbuilder 4mo ago
  Yeah, it's actually the case. Researchers have shown that the models response doesn't always follow from the reasoning. Whether you consider that an internal language or not really depends on what you're speculating the neural network is doing. I think there was an Antropic paper on it.
- wolttam 4mo ago
  The parent is off, you’re right. They may reason in any language, typically whatever the user’s language is, and you’ll see the reasoning directly with an open model like Deepseek. Research only showed that thinking might be disconnected from the final output but in my experience they are very strongly correlated in recent models
  - fc417fc802 4mo ago
    > Research only showed that thinking might be disconnected from the final output It is trivial to regularly spot obvious contradictions and inconsistencies if you read carefully. For example I've encountered traces that amounted to "I can deduce X, therefore Y, so that means Z" but then the model turns around and outputs "the answer is W because X". It's even been demonstrated that having the model output placeholder tokens or other gibberish instead of "thoughts" still improves performance. However the thinking traces can still be useful to the end user regardless.
deleted 4mo ago
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phi0 4mo ago
This is inaccurate. The displayed reasoning traces are summaries, but the model thinks in nominally regular human languages. AI labs are very light on details (as they consider them as their "edge"), but both GPT5.5 and Claude Mythos/Fable system cards discuss chain-of-thought monitorability quite a bit. They occasionally show snippets of CoT in papers they write, e.g. for o3/o4/GPT5 models [1] or Claude 3.5 Haiku [2]. [1]: https://openai.com/index/evaluating-chain-of-thought-monitorability/ https://openai.com/index/evaluating-chain-of-thought-monitor... [2]: https://transformer-circuits.pub/2025/attribution-graphs/biology.html https://transformer-circuits.pub/2025/attribution-graphs/bio...

seydor 4mo ago

> summaries generated Or hallucinated

dryarzeg 4mo ago

As far as I'm aware, it's not true for models like DeepSeek or other Chinese open-weight models (at least those that I have seen); their reasoning traces are fully composed from some human language, be it English, Chinese or another one; by the way, most of them can adapt their reasoning based on user language, for example, if user speaks English the reasoning more likely will be in English. I think that for DeepSeek problem (thinking and replying in Chinese) everything is kinda simpler: in their official chat, they're probably using some kind of system prompt which is (probably) written in Chinese, so that's why model may prefer Chinese in it's output.

calgoo 4mo ago
I have seen mixed language thinking from claude when i speak to it in english but we are discussing a product thats in spanish or searching amazon spain.

kgeist 4mo ago

Summaries by different smaller models are usually made by closed proprietary models like Claude as a way to combat the distillation of real reasoning traces by competitors. Open weight models show the real reasoning traces. Reasoning traces operate in the same space as the non-reasoning output. It's all just one large text for an LLM. Internally, reasoning is just ordinary chat completion between <think></think> tags.

ForceBru 4mo ago

Wait, this isn't real, is it? Is there actually an intermediate model that translates DeepSeek's thinking from its "alien language" into human languages? That's not actually the case, right? I thought "thinking" is literally the model generating additional text in a human language that shows its "thought process". It's added to the model's context, which helps it reason better because it now has this self-generated context. The "their own language" idea seems to come from some recent science fiction where LLMs develop their alien language and take over the world by 2037 or something.

Gracana 4mo ago
You're right, it's just additional text that allows it to do thinking / reasoning-like behavior. The big proprietary models hide the real output from the user and instead provide a friendly abridged version, but that's just to protect their secret sauce from distillation.
mcbuilder 4mo ago
Yeah, it's actually the case. Researchers have shown that the models response doesn't always follow from the reasoning. Whether you consider that an internal language or not really depends on what you're speculating the neural network is doing. I think there was an Antropic paper on it.
wolttam 4mo ago
The parent is off, you’re right. They may reason in any language, typically whatever the user’s language is, and you’ll see the reasoning directly with an open model like Deepseek. Research only showed that thinking might be disconnected from the final output but in my experience they are very strongly correlated in recent models
- fc417fc802 4mo ago
  > Research only showed that thinking might be disconnected from the final output It is trivial to regularly spot obvious contradictions and inconsistencies if you read carefully. For example I've encountered traces that amounted to "I can deduce X, therefore Y, so that means Z" but then the model turns around and outputs "the answer is W because X". It's even been demonstrated that having the model output placeholder tokens or other gibberish instead of "thoughts" still improves performance. However the thinking traces can still be useful to the end user regardless.

deleted 4mo ago

[deleted]

phi0 4mo ago

This is inaccurate. The displayed reasoning traces are summaries, but the model thinks in nominally regular human languages. AI labs are very light on details (as they consider them as their "edge"), but both GPT5.5 and Claude Mythos/Fable system cards discuss chain-of-thought monitorability quite a bit. They occasionally show snippets of CoT in papers they write, e.g. for o3/o4/GPT5 models [1] or Claude 3.5 Haiku [2]. [1]: https://openai.com/index/evaluating-chain-of-thought-monitorability/ https://openai.com/index/evaluating-chain-of-thought-monitor... [2]: https://transformer-circuits.pub/2025/attribution-graphs/biology.html https://transformer-circuits.pub/2025/attribution-graphs/bio...