IntelliFold (AlphaFold3)
Open-source AlphaFold3-class model (IntelliFold) with fast, accurate structure prediction across biomolecules.
Overview
IntelliFold is a next-generation open-source foundation model for 3D biomolecular structure prediction, delivering AlphaFold3-level accuracy across proteins, nucleic acids, and small molecules. Through architectural innovations like a high-speed FlashAttentionPairBias kernel and a training-free, model-agnostic ranking method, IntFold achieves fast, accurate, and clash-free structure generation.
Run IntelliFold (AlphaFold3) on Neurosnap
The IntelliFold (AlphaFold3) online webserver allows anybody with a Neurosnap account to run and access IntelliFold (AlphaFold3), no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- Custom FlashAttentionPairBias kernel for faster, memory-efficient inference on large biomolecular systems.
- Model-agnostic, training-free ranking via structural self-consistency improves prediction quality.
- High-accuracy all-atom prediction across proteins, nucleic acids, and small molecules.
- Success rates matching AlphaFold 3 on FoldBench benchmark for protein and RNA complexes.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access IntelliFold (AlphaFold3) using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using IntelliFold (AlphaFold3) in publications or research outputs.
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Team TI, Qiao L, Bai W, Yan H, Liu G, Xi N, Zhang X. IntFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction. arXiv preprint arXiv:2507.02025. 2025 Jul 2. |
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Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2022). ColabFold: making protein folding accessible to all. Nature Methods. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |