LICENSE

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.