AxionLab-official/Axion1.5-0.3B-Base

Axion1.5-0.3B-Base

🧠 Axion1.5-0.3B-Base is a base language model with approximately 300 million parameters, trained purely for next-token prediction.

No instruction tuning. No reinforcement learning. No forced reasoning chains.

Just raw language modeling.

This model exists with a clear goal: to act as a clean, transparent baseline for future experiments focused on explicit reasoning and structured thinking.

What this model is

A foundation / base model

Trained only with next-token prediction

Not optimized for chat or instruction-following

Designed as a reference point for research and comparison

A functional “blank mind” before reasoning specialization

What this model is not

❌ Not a chatbot

❌ Not instruction-tuned

❌ Not aligned for safety or helpfulness

❌ Not optimized for long conversations

❌ Not a reasoning model (yet)

If you are looking for a model that follows instructions or explains its thoughts, this is not it.

Why release a base model?

Releasing the base model publicly allows:

Transparent evaluation of raw language modeling quality

Fair comparison with future Axion reasoning variants

Reproducibility and honest benchmarking

A clear separation between language competence and reasoning behavior

Many projects hide their base models. Axion does the opposite.

Intended use

Research and experimentation

Fine-tuning for instruction-following or reasoning tasks

Studying the effects of reasoning-oriented datasets

Serving as a backbone for Axion1.5-Reasoning variants

Limitations

Because this model is trained only for next-token prediction:

It may produce incoherent or incomplete responses

It does not reliably follow instructions

It does not reason step-by-step

It may hallucinate or contradict itself

These limitations are expected and acknowledged.

**Future work

This release is part of a broader project:

Axion1.5-Reasoning – fine-tuned for structured reasoning

Axion-Critic – models focused on evaluation and self-critique

Experiments with short, verifiable reasoning traces

The base model will remain unchanged to preserve its value as a reference.

Philosophy

Scale is not intelligence. Structure matters.

Axion explores whether smaller models, trained with the right constraints, can develop more meaningful reasoning behaviors.

This is an experiment. And experiments are allowed to fail.

Acknowledgements

Created as an independent research project focused on understanding how reasoning emerges in language models.