Why Are There No Latent Reasoning Models?
Published:Dec 27, 2025 14:26
•1 min read
•r/singularity
Analysis
This post from r/singularity raises a valid question about the absence of publicly available large language models (LLMs) that perform reasoning in latent space, despite research indicating its potential. The author points to Meta's work (Coconut) and suggests that other major AI labs are likely exploring this approach. The post speculates on possible reasons, including the greater interpretability of tokens and the lack of such models even from China, where research priorities might differ. The lack of concrete models could stem from the inherent difficulty of the approach, or perhaps strategic decisions by labs to prioritize token-based models due to their current effectiveness and explainability. The question highlights a potential gap in current LLM development and encourages further discussion on alternative reasoning methods.
Key Takeaways
- •Latent space reasoning in LLMs is an area of active research.
- •The lack of publicly available models may be due to technical challenges or strategic decisions.
- •The interpretability of tokens may be a factor in the preference for token-based models.
Reference
“"but why are we not seeing any models? is it really that difficult? or is it purely because tokens are more interpretable?"”