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# AlphaFold 3 still leads FoldBench at 64.9%; the best 2025 model, SeedFold, scored 63.1%
- URL: https://aiadoption.org/data/foldbench-cofolding-accuracy/
- Published: 2026-10-19T16:36:44.000Z
- Updated: 2026-10-21T06:05:03.000Z
- Description: AlphaFold 3 scored 64.9% on FoldBench, which tests how well models predict how small molecules bind to proteins. None of the four 2025 models in the data beat it; SeedFold came closest at 63.1%.
- Author: Manu
- Tags: Data, AI in Healthcare, #chart, #ai-index-2026, #hub-healthcare

64.9%

#1 of 8

AlphaFold 3's FoldBench accuracy (2024, 370M parameters), the highest of eight models; SeedFold (2025, 923M) scored 63.1%

FoldBench accuracy

AlphaFold 3 (2024)64.9%

SeedFold (2025)63.1%

RosettaFold-3 (2025)57.3%

## What the chart shows

FoldBench tests whether a model correctly predicts how a small molecule, such as a drug candidate, binds to a target protein. AlphaFold 3, released in May 2024 with 370 million parameters, scored 64.9%, the highest of the eight models in the data.

SeedFold (December 2025, 923 million parameters) came closest at 63.1%, followed by RosettaFold-3 (57.3%). Five later models are larger than AlphaFold 3 without scoring higher, which the AI Index reads as a sign that training data, not size, is the bottleneck.

## Key numbers

| Measure                    | Value  |
| -------------------------- | ------ |
| AlphaFold 3 (2024, 370M)   | 64.90% |
| SeedFold (2025, 923M)      | 63.10% |
| RosettaFold-3 (2025, 730M) | 57.28% |
| Boltz-1 (2024, 610M)       | 55.04% |
| Boltz-2 (2025, 521M)       | 53.90% |
| Protenix v0.7 (2025, 368M) | 50.70% |

## How to read it

- Accuracy on FoldBench’s small-molecule binding tasks as compiled by RAISE Health; scores on other cofolding tasks can rank models differently.
- Parameter counts are in the CSV; Protenix v0.7 is listed at 368M here and 370M in the model-size data.

**Source:** [RAISE Health](https://aiadoption.org/sources/#raise-health), 2026, via the AI Index Report 2026 (Stanford HAI), figure 6.1.9: *FoldBench: protein cofolding performance, 2024–25*. Chart and text by AI Adoption.  
Numbers checked against the published data on 20 October 2026.  
[Download the data (CSV)](https://charts.aiadoption.org/ai-index/csv/foldbench-cofolding-accuracy.csv?ref=aiadoption.org) · [Cite this chart](#source)