Dataset Card for GPQA

GPQA is a multiple-choice, Q&A dataset of very hard questions written and validated by experts in biology, physics, and chemistry. When attempting questions out of their own domain (e.g., a physicist answers a chemistry question), these experts get only 34% accuracy, despite spending >30m with full access to Google. We request that you do not reveal examples from this dataset in plain text or images online, to reduce the risk of leakage into foundation model… See the full description on the dataset page: https://huggingface.co/datasets/Idavidrein/gpqa.

math-ai/gpqa dataset hosted on Hugging Face and contributed by the HF Datasets community

Comparison of Independently conducted by Artificial Analysis by Model

This dataset is a reformatted version of the original GPQA dataset from Idavidrein/gpqa. It includes only the main question, four shuffled answer choices, the correct answer index, subdomain, and a unique id for each entry.Please cite the GPQA paper if you use this data: GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Comparison of GPQA Diamond (Scientific Reasoning) by Model

ko-gpqa

ko-gpqa is a Korean-translated version of the GPQA (Graduate-Level Google‑Proof Q&A) benchmark dataset, which consists of high-difficulty science questions. Introduced in this paper, GPQA is designed to go beyond simple fact retrieval and instead test an AI system’s ability to perform deep understanding and logical reasoning. It is particularly useful for evaluating true comprehension and inference capabilities in language models. The Korean translation was performed using… See the full description on the dataset page: https://huggingface.co/datasets/davidkim205/ko-gpqa.

fingertap/GPQA-Diamond dataset hosted on Hugging Face and contributed by the HF Datasets community

Comparison of model accuracy on GPQA, token pricing, and latency for leading AI reasoning models.

dogtooth/gpqa dataset hosted on Hugging Face and contributed by the HF Datasets community

rl-actors/Chemistry-GPQA dataset hosted on Hugging Face and contributed by the HF Datasets community

Comparison of Artificial Analysis Intelligence Index v2.2 incorporates 8 evaluations: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME, IFBench, AA-LCR by Model

rl-actors/Biology-GPQA dataset hosted on Hugging Face and contributed by the HF Datasets community

GPA reported 2.64 in PE Price to Earnings for its fiscal quarter ending in September of 2024. Data for GPA | PCAR3 - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last August in 2025.

Dimers of transmembrane (TM) peptides based on the Glycophorin A (GpA) dimer are simulated in different membrane environments. Three different homodimers with varying TM domain lengths and one heterodimer are considered. The homodimers are formed of either

• 17L (GRPNLKLLLGVLLGVLLTLLLLEYP)
• 23L (GRPNLKLLLLLLGVLLGVLLTLLLLLLLEYP)
• 29L (GRPNLKLLLLLLLLLGVLLGVLLTLLLLLLLLLLEYP)

peptides, while the heterodimer consists of one 17L peptide and one 29L peptide. In the sequences, the bold letters denote the amino acids involved in the GpA dimerization motif. The dimers are simulated in DLPC (12:0 PC), DOPC (18:1 PC), or DEPC (22:1 PC) bilayers. Additionally, a polyleucine dimer is simulated in a DOPC bilayer. Bilayers consist of 400 lipids and they are adequately hydrated with 24000 water molecules and 134 mM NaCl. The simulations are 100 ns long with trajectories written every 100 ps.

The files are named as XXX-YYYY.ZZZ, where XXX denotes to the peptide type ('het' for the heterodimer and 'polyl' for the polyleucine), YYYY denotes the bilayer type, and ZZZ denotes the file type. Files are in Gromacs format: .xtc for trajectories, .edr for energy data, .cpt for continue points, .ndx for index files, .top for topology files, and .tpr for run input files (Gromacs 5.1). The simulation parameter file (md.mdp) is common for all systems. The CHARMM36 force field is used; topologies are obtained from CHARMM-GUI, and those of the peptides are included in Gromacs format (.itp).

More information on the systems is available in the publication, available here: (TO BE INCLUDED!)

Note that the data for the heterodimer and for the polyleucine are in part 2/2, available at https://doi.org/10.5281/zenodo.573274

GPA reported BRL4.77B in Sales Revenues for its fiscal quarter ending in March of 2025. Data for GPA | PCAR3 - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last September in 2025.

Comparison of Artificial Analysis Intelligence Index v2.2 incorporates 8 evaluations: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME, IFBench, AA-LCR by Model

GPA reported BRL-0.03 in EPS Earnings Per Share for its fiscal quarter ending in March of 2025. Data for GPA | PCAR3 - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last September in 2025.

GPA reported BRL490.29M in Ordinary Share Capital for its fiscal quarter ending in March of 2025. Data for GPA | PCAR3 - Ordinary Share Capital including historical, tables and charts were last updated by Trading Economics this last September in 2025.

This dataset provides the number and total area of properties managed by GPA.

Recently we studied L-alanine to 9.85 GPa. This is the highest pressure for which structural data are available for any organic system larger than methane. The results enabled us to disprove claims made for a phase transition at 2 GPa. Neither was a previously proposed phase transition at 9 GPa observed, though this may be a deuteration effect. At 9.85 GPa the cell volume is 75% of its ambient-pressure value; the NH¿O H-bonds are amongst the shortest yet observed. The powder pattern remains sharp, however, and we now propose to explore the behaviour of alanine at still higher pressure. This will be the first study on a complex H-bonded organic solid beyond 10 GPa, and the results will be fascinating in revealing the effects on the H-bonding and phase behaviour of a complex molecular syetem.