Axion-1.0

Paper · Project · Code · Training Data

This repository provides a reproduction checkpoint of Axion 1.0-35B, following the recipe described in Axion 1.0: Open Agent Foundation Models, Simplified. The model is designed for scientific reasoning, information seeking, and tool-augmented problem solving.

Model Overview

The training recipe combines approximately 18K SFT examples with three stages:

1. Learn to reason: supervised fine-tuning on challenging, self-contained scientific problems constructed with model-aware feedback.
2. Learn to investigate: supervised fine-tuning on verifiable tasks requiring external information and tool use.
3. Learn through interaction: reinforcement learning over agent trajectories to refine reasoning and interaction with tools.

Performance

The table compares paper-reported results with the results of the reproduction checkpoint released in this repository. All scores are percentages; higher is better.

HLE denotes the full Humanity's Last Exam benchmark; BMB uses the human-difficult BioMysteryBench subset. FS denotes FrontierScience. A dash indicates an unreported result. Bold highlights the reproduction checkpoint released in this repository.

Usage

Following the repository's inference guide, serve the released checkpoint with vLLM:

vllm serve Axion1-0/Axion-1.0-35B \
  --served-model-name axion-35b \
  --host 127.0.0.1 --port 8000 \
  --tensor-parallel-size 8 --dtype bfloat16 \
  --max-model-len 131072 \
  --reasoning-parser qwen3 \
  --enable-auto-tool-choice --tool-call-parser qwen3_coder

This example uses eight GPUs. Adjust tensor parallelism and context capacity to fit your GPU memory.

Call the OpenAI-compatible endpoint:

curl --fail-with-body http://127.0.0.1:8000/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "axion-35b",
    "messages": [
      {"role": "user", "content": "What is 2 + 3?"}
    ],
    "max_tokens": 1024
  }'

Tool-using agent evaluation additionally requires a harness that executes tool calls. See the inference guide for details.

License

This model is released under the Apache License 2.0. See LICENSE for details.

Citation

@misc{jia2026axion,
  title         = {Axion 1.0: Open Agent Foundation Models, Simplified},
  author        = {Yuqi Jia and Yunjie Tian and Jiayu Zheng and Yijun Liang and Jingchen Sun and Mengyu Zhao and Di Fu},
  year          = {2026},
  eprint        = {2611.03233},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  url           = {https://arxiv.org/abs/2611.03233}
}