TUM Tadpole
Hugging Face: https://huggingface.co/thuerey-group/Tadpole
GitHub: https://github.com/tum-pbs/Tadpole
Website: https://ge.in.tum.de/2026/05/18/tadpole-flexible-scientific-foundation-models/
Technical report: https://arxiv.org/abs/2605.15284
Developer: Thuerey Group, Technical University of Munich
Released: May 2026
Variants: S, B, L; only B weights released
Parameters: S: 8.8M / B: 38.1M / L: 152.1M
Resolution: pre-trained at 64, 128, 256 and 384 cubed, evaluated to 1024 cubed
Architecture: 3D PDE autoencoder pre-trained on single-channel 64x64x64 crops, P3D hybrid backbone with convolutional stages and a transformer bottleneck, adversarial reconstruction loss; latent compression 16 (S) / 8 (B) / 4 (L); Tadpole-DFT adds LoRA, a latent dynamics sub-network, and zero-initialized skip connections for rollout
License: Apache 2.0
Modalities: 3D PDE fields in, 3D PDE fields out
Runs on: Autoencoding: Laptop / Dynamics: Desktop GPU, NVIDIA only
Formats: safetensors, separate encoder and decoder
On disk: B: 60.4MB encoder, 92.6MB decoder