June 9 Researcher Reciprocity License Version 1.0 dated June 9, 2026 This is a license (the "License") between you ("You") and GPU Mode and the KernelBot dataset contributors ("Licensor"). This License adapts the Open Responsible AI License Data ("Open RAIL-D") pattern for a dataset artifact and adds the Researcher Reciprocity use restriction in Attachment A. It is intended to have an open and permissive character while preserving reciprocal research access when the Dataset is used to train or improve AI systems. If you train on it, you let us generate. Section I: Preamble KernelBot is a competition platform for writing heterogeneous GPU code. The Dataset contains submissions, metadata, benchmark results, and related materials from KernelBot competitions. Licensor wishes to promote collaboration, open research, education, benchmarking, and broad reuse of the Dataset. Licensor also wishes to avoid a one-way bargain in which researchers and contributors publish ideas and code that are used to improve AI systems, while the providers of those AI systems then prohibit those same researchers from generating outputs, evaluating the systems, benchmarking them, publishing research, or exploring their own ideas. This License therefore grants broad rights to use the Dataset, subject to attribution and the use-based restriction in Attachment A. Section II: Definitions 1. "License" means these terms and conditions for use, reproduction, and Distribution. 2. "Dataset" means the files, records, metadata, documentation, and other materials distributed with this License. 3. "Output" means the results of operating a model, service, application, or other system. 4. "Model" means any machine-learning or artificial-intelligence based assemblies, including model weights, checkpoints, parameters, optimizer states, adapters, embedding systems, agents, APIs, hosted services, or other systems that are trained, tuned, evaluated, benchmarked, or otherwise used in connection with the Dataset. 5. "Derivatives of the Dataset" means all modifications, transformations, annotations, translations, extracts, subsets, compilations, arrangements, or other works based on the Dataset. 6. "Derivatives of a Model" means all modifications to a Model, works based on a Model, or any other model that is created or initialized by transfer of patterns of weights, parameters, activations, embeddings, outputs, or other representations of the Model, including distillation methods and methods based on synthetic data generated by the Model. 7. "Training Use" means using the Dataset, in whole or in part, to train, pretrain, fine-tune, post-train, align, distill, evaluate for training, benchmark for training, generate synthetic data for training, construct embeddings for training, rank or filter examples for training, or otherwise improve the weights, behavior, capabilities, or performance of a Model or Derivatives of a Model. 8. "Covered Model" means any Model or Derivatives of a Model that is trained, fine-tuned, distilled, aligned, evaluated for training, benchmarked for training, or otherwise improved through Training Use of the Dataset. 9. "Distribution" means any transmission, reproduction, publication, hosting, or other sharing of the Dataset, Derivatives of the Dataset, a Covered Model, or Derivatives of a Covered Model to a third party, including making any of them available by electronic or remote means, such as API-based or web access. 10. "Licensor" means GPU Mode, the dataset maintainers, and any contributor who has authority to license their contribution under these terms. 11. "You" or "Your" means an individual or legal entity exercising permissions granted by this License or making use of the Dataset for any purpose. 12. "Third Parties" means individuals or legal entities that are not under common control with Licensor or You. 13. "Authorized Researchers" means GPU Mode, the dataset maintainers, dataset contributors, and any researchers or organizations that GPU Mode designates in writing for purposes of generating outputs from, evaluating, benchmarking, auditing, criticizing, or publishing research about a Covered Model. 14. "Ordinary Users" means the general class of users to whom You make a Covered Model available, including through a public product, commercial product, research release, API, hosted service, preview, beta, or gated access program. Section III: Intellectual Property Rights 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Licensor grants You a worldwide, non-exclusive, no-charge, royalty-free copyright license to reproduce, prepare derivative works of, publicly display, publicly perform, sublicense, and distribute the Dataset and Derivatives of the Dataset. 3. No Patent License. This License does not grant any patent license. Section IV: Conditions of Usage, Distribution, and Redistribution 4. Distribution and Redistribution. You may reproduce and distribute copies of the Dataset or Derivatives of the Dataset in any medium, with or without modifications, provided that You meet the following conditions: 4.1. You must give Third Party recipients of the Dataset or Derivatives of the Dataset a copy of this License or a clear link to it. 4.2. You must retain reasonable copyright, license, and attribution notices, excluding notices that do not pertain to any part of the Dataset or Derivatives of the Dataset. 4.3. You must give reasonable attribution to GPU Mode and the KernelBot dataset. Reasonable attribution includes, where practical, the dataset name, a link to the dataset source, and any citation requested in the Dataset documentation. 4.4. You must cause any modified files, datasets, or documentation that You Distribute to carry prominent notices stating that You changed them. 4.5. You may add Your own copyright statement to Your modifications and may provide additional or different license terms for Your independent additions, annotations, analyses, software, models, outputs, or other works, provided that Your use, reproduction, and Distribution of the Dataset otherwise complies with this License. 5. Use-Based Restrictions. The restriction set forth in Attachment A is a use-based restriction. You may not use the Dataset, Derivatives of the Dataset, Covered Models, or Derivatives of Covered Models for the restricted use specified in Attachment A. For Training Use, the use-based restriction in Attachment A must be included as an enforceable provision in any legal agreement, terms of use, acceptable use policy, license, or other terms governing the use or Distribution of a Covered Model or Derivatives of a Covered Model. You must give notice to subsequent users that the Covered Model or Derivatives of the Covered Model are subject to Attachment A. 6. Outputs. Except as stated in this License, Licensor claims no rights in the Output You generate using a Covered Model. You are accountable for the Output You generate and its subsequent uses. No use of the Output may contravene this License. Section V: Other Provisions 7. No Endorsement. Nothing in this License permits You to use Licensor's names, logos, trademarks, or service marks to imply endorsement, sponsorship, or approval. 8. Third-Party Rights. The Dataset may include material submitted by third parties. This License applies only to rights that Licensor has authority to license. You are responsible for complying with any third-party rights, privacy obligations, laws, or regulations that apply to Your use. 9. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Dataset on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, ACCURACY, AVAILABILITY, OR ABSENCE OF DEFECTS. You are solely responsible for determining the appropriateness of using or redistributing the Dataset and assume any risks associated with Your exercise of permissions under this License. 10. Limitation of Liability. To the maximum extent permitted by law, in no event and under no legal theory, whether in tort, contract, or otherwise, unless required by applicable law or agreed to in writing, shall any Licensor or contributor be liable to You for damages, including direct, indirect, special, incidental, consequential, exemplary, or punitive damages arising as a result of this License or out of the use or inability to use the Dataset, even if such Licensor or contributor has been advised of the possibility of such damages. 11. Accepting Warranty or Additional Liability. While redistributing the Dataset or Derivatives of the Dataset, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any Licensor or contributor, and only if You agree to indemnify, defend, and hold each Licensor and contributor harmless for any liability incurred by, or claims asserted against, such Licensor or contributor by reason of Your accepting any such warranty or additional liability. 12. Termination. If You violate this License, Your rights under it terminate automatically. For violations other than violations of Attachment A, Your rights are reinstated if You cure the violation within 30 days after discovering it or receiving written notice from Licensor. For violations of Attachment A involving a Covered Model, Your Training Use rights terminate automatically as to the affected Covered Model and may be reinstated only if Licensor provides written reinstatement or waiver. 13. Severability. If any provision of this License is held invalid, illegal, or unenforceable, the remaining provisions remain valid as if the provision had not been set forth. The unenforceable provision will be interpreted or reformed only to the minimum extent necessary to make it enforceable while preserving its purpose. 14. Additional Permission. Licensor may grant additional permissions, exceptions, waivers, commercial terms, or private licenses in writing. Those permissions apply only to the recipient and scope stated in the written grant. End of Terms and Conditions Attachment A Use Restriction: Researcher Reciprocity for Training Use You agree not to use the Dataset or Derivatives of the Dataset for Training Use if You make the resulting Covered Model or Derivatives of the Covered Model available under terms, policies, technical measures, access rules, account restrictions, acceptable-use rules, or other conditions that prohibit, penalize, or materially burden Authorized Researchers from: 1. generating outputs from the Covered Model; 2. evaluating, auditing, red-teaming, or benchmarking the Covered Model; 3. comparing the Covered Model to other systems; 4. publishing research, criticism, measurements, benchmark results, or analysis concerning the Covered Model; or 5. using the Covered Model to explore, test, or develop their own research ideas. This access must be available on materially equal terms to those offered to Ordinary Users of the Covered Model, subject only to neutral limits that apply equally to Ordinary Users, such as generally applicable rate limits, payment terms, safety rules, security rules, and laws. Any terms, policies, technical measures, access rules, account restrictions, acceptable-use rules, or other conditions that conflict with this Attachment A make the Covered Model ineligible for the Training Use grant unless Licensor has waived the conflict in writing. You may not suspend, ban, throttle, sue, threaten, or otherwise retaliate against Authorized Researchers solely because they engage in the activities listed in this Attachment A, provided that their activity complies with generally applicable law and neutral safety or security rules that are also applied to Ordinary Users.