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Release 2.5.0

Summary

This release extends GPU support with NVIDIA B300 and GB300, and removes the per-GPU engine-build step that was required by earlier releases. OpenFold2 now starts and serves requests with a single, simplified runtime configuration.

Key Features

  • NVIDIA B300: Added support for NVIDIA B300 GPU (288GB HBM3e)
  • NVIDIA GB300: Added support for NVIDIA GB300 Grace Blackwell Ultra superchip (288GB HBM3e)
  • Confidence outputs (pLDDT, PAE, pTM): Each predicted structure in structures_in_ranked_order now includes per-residue plddt, the predicted_aligned_error matrix and its max_predicted_aligned_error bin upper bound, aligned_confidence_probs, and the ptm_score confidence scalar. Refer to Response Fields in Example Requests and the API Reference for field-by-field details.
  • New optimized inference backend: The NIM now runs on a fully NVIDIA-tuned inference path, delivering faster and more consistent predictions out of the box.

Backend Optimizations

The new inference backend introduces custom GPU kernels and graph-level optimizations:

  • New kernels: Fused Adaptive Layer Norm; DualGemm (sm80, two variants); gated sigmoid (sm80); FlashAttention v2/v3 for Triangle Attention and Attention Pair Bias.
  • Pre-computed masks and buffers: Pre-computed, left-aligned attention masks feed directly into the new dual-GEMM and attention kernels, with pre-computed buffers for the Pairformer and Diffusion Transformer (DiT) stacks.