ExoMind: Democratizing Scientific Intelligence via Extended-Mind-Inspired Agentic System
ExoMind Team · Shanghai Artificial Intelligence Laboratory
🔥 News
- 2026-08-28: 🔥 The ExoMind preprint is now available on Preprints.org.
- 2026.8.25: 🔥 We have released a series of official GGUF variants for ExoMind and ExoMind-9B. Please refer to the ExoMind collection. We also thank mradermacher for providing additional GGUF quantizations, including both static and importance-matrix variants: ExoMind-i1-GGUF, ExoMind-GGUF, ExoMind-9B-i1-GGUF, and ExoMind-9B-GGUF.
- 2026-08-12: We release the official project page and public repository.
Overview
ExoMind-9B is the compact ExoMind checkpoint, fine-tuned from Qwen3.5-9B for lower-resource experimentation in scientific reasoning and agentic research. It follows the same extended-mind-inspired approach, organizing the model, specialized interaction objects, and autonomous interaction processes as one system.
Highlights
- Compact scientific checkpoint: supports resource-conscious experiments with the ExoMind reasoning and interaction paradigm.
- Scientific interaction: works with source discovery, evidence grounding, executable verification, and observation integration workflows.
- Progressive CoI training: develops intrinsic reasoning and interaction behavior from selected pure-reasoning and interaction trajectories.
- Multimodal foundation: retains the image-text capabilities of its Qwen3.5 base model.
Quick Start
Use a recent vLLM or SGLang release with Qwen3.5 support. The examples below use the checkpoint's configured maximum context length of 262,144 tokens.
vLLM
vllm serve AI4SGI/ExoMind-9B \
--port 8000 \
--tensor-parallel-size 1 \
--max-model-len 262144 \
--reasoning-parser qwen3 \
--enable-auto-tool-choice \
--tool-call-parser qwen3_coder
SGLang
python -m sglang.launch_server \
--model-path AI4SGI/ExoMind-9B \
--host 0.0.0.0 \
--port 8000 \
--tp-size 1 \
--context-length 262144 \
--reasoning-parser qwen3 \
--tool-call-parser qwen3_coder
OpenAI-Compatible API
from openai import OpenAI
client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
response = client.chat.completions.create(
model="AI4SGI/ExoMind-9B",
messages=[
{
"role": "user",
"content": "Develop a testable hypothesis and a rigorous verification plan for: ...",
}
],
temperature=1.0,
top_p=0.95,
extra_body={"top_k": 20},
)
print(response.choices[0].message.content)
Evaluation
The table below reports the main ExoMind 35B-A3B system. ExoMind-9B is provided as a compact checkpoint and has not been assigned these scores.
Complete settings and comparisons are available in the evaluation explorer.
Intended Use
ExoMind-9B is intended for scientific question answering, mathematical and computational reasoning, tool-use experiments, code-assisted verification, and resource-conscious agentic prototypes.
License and Attribution
The distributed checkpoint and upstream Qwen3.5 materials are provided under the Apache License 2.0 included in this repository. The preprint, scientific figures and results, and ExoMind brand assets are subject to the ExoMind Research Content and Brand Terms. See NOTICE.md for third-party notices.
Citation
@article{Ye_2026,
title = {ExoMind: Democratizing Scientific Intelligence via Extended-Mind-Inspired Agentic System},
author = {Ye, Peng and Liu, Zhuo and Ye, Jingqi and Yu, Fangchen and Tang, Shengji and Jiang, Yichen and He, Haonan and Cao, Zongsheng and Chen, Tao and Zhang, Bo and Ouyang, Wanli and Zhou, Bowen and Bai, Lei},
year = {2026},
month = aug,
publisher = {MDPI AG},
doi = {10.20944/preprints202608.2038.v1},
url = {https://doi.org/10.20944/preprints202608.2038.v1}
}