TNSA Legal Center

Policies, terms, and compliance information for TNSA. Browse categories or jump to a specific topic.

TNSA OpenWeight Model Licensing Framework

Comprehensive licensing terms, obligations, and attribution requirements for all TNSA OpenWeight AI models and derivatives. Version 5.3 — Effective December 9, 2025

OpenWeight Licensing Overview

1. License Definitions & Scope2. Covered Model Categories3. Granted Permissions4. Usage Restrictions5. Attribution Requirements6. Derivative Works7. Commercial Usage Terms8. Compliance & Monitoring9. License Termination10. Liability & Warranties

1. LICENSE DEFINITIONS & SCOPE

1.1 Core Definitions

  • 1.1.1 "OpenWeight Models" means AI models where TNSA has made model weights, parameters, and architecture publicly available under open licensing terms.
  • 1.1.2 "Model Weights" means the learned parameters, coefficients, and numerical values that define the behavior and capabilities of an AI model.
  • 1.1.3 "Model Architecture" means the structural design, layer configuration, and computational framework of an AI model.
  • 1.1.4 "Training Code" means software, scripts, and procedures used to train, fine-tune, or modify AI models.
  • 1.1.5 "Inference Code" means software required to load, execute, and generate outputs from AI models.
  • 1.1.6 "Model Card" means documentation describing model capabilities, limitations, training data, and intended use cases.
  • 1.1.7 "Derivative Model" means any AI model created by modifying, fine-tuning, or building upon TNSA OpenWeight Models.
  • 1.1.8 "Commercial Use" means any use of OpenWeight Models for commercial purposes, including but not limited to revenue generation, business operations, or competitive advantage.
  • 1.1.9 "Research Use" means use for academic research, scientific investigation, or educational purposes without commercial intent.
  • 1.1.10 "Distribution" means making OpenWeight Models or derivatives available to third parties through any means.

1.2 License Scope

  • 1.2.1 This license applies to all TNSA OpenWeight Models and associated materials made available under open licensing terms.
  • 1.2.2 The license covers model weights, architectures, training code, inference code, and documentation.
  • 1.2.3 Different license terms may apply to different model versions or releases.
  • 1.2.4 Supplemental terms may apply to specific models or use cases as indicated in model documentation.
  • 1.2.5 This license does not grant rights to TNSA trademarks, service marks, or proprietary branding.
  • 1.2.6 Training data used to create OpenWeight Models may be subject to separate licensing terms.
  • 1.2.7 Third-party components integrated into OpenWeight Models retain their original licensing terms.
  • 1.2.8 Geographic restrictions may apply based on export control laws and regulations.
  • 1.2.9 Temporal limitations may apply to certain license grants or model versions.
  • 1.2.10 Updates and modifications to licensing terms will be communicated through official TNSA channels.

1.3 License Types

  • 1.3.1 "TNSA Open License" - Permissive license allowing broad commercial and research use with attribution.
  • 1.3.2 "TNSA Research License" - License restricted to non-commercial research and educational use.
  • 1.3.3 "TNSA Community License" - License for community-driven development with share-alike provisions.
  • 1.3.4 "TNSA Evaluation License" - Time-limited license for evaluation and testing purposes.
  • 1.3.5 "TNSA Custom License" - Negotiated license terms for specific use cases or organizations.

2. COVERED MODEL CATEGORIES

2.1 NGen Series Models

  • 2.1.1 NGen3 OpenWeight Models - Latest generation large language models with full commercial licensing.
  • 2.1.2 NGen2 OpenWeight Models - Previous generation models with continued support and licensing.
  • 2.1.3 NGen Base Models - Foundation models suitable for fine-tuning and specialization.
  • 2.1.4 NGen Instruct Models - Instruction-tuned variants optimized for conversational use.
  • 2.1.5 NGen Code Models - Specialized variants trained for code generation and programming tasks.
  • 2.1.6 NGen Reasoning Models - Enhanced variants with improved logical reasoning capabilities.
  • 2.1.7 NGen Multimodal Models - Models capable of processing text, images, and other modalities.
  • 2.1.8 NGen Domain Models - Specialized models for specific industries or use cases.
  • 2.1.9 NGen Efficient Models - Optimized variants for resource-constrained environments.
  • 2.1.10 NGen Experimental Models - Research variants with novel architectures or capabilities.

2.2 IGen Series Models

  • 2.2.1 IGen 1 Nano Models - Compact image generation models for edge deployment.
  • 2.2.2 IGen Base Models - Foundation models for image synthesis and manipulation.
  • 2.2.3 IGen Style Models - Specialized models for artistic and stylistic image generation.
  • 2.2.4 IGen Photo Models - Photorealistic image generation models with high fidelity output.
  • 2.2.5 IGen Edit Models - Models specialized for image editing and modification tasks.
  • 2.2.6 IGen Upscale Models - Super-resolution models for image enhancement and upscaling.
  • 2.2.7 IGen Inpaint Models - Models for image inpainting and completion tasks.
  • 2.2.8 IGen Control Models - Models with enhanced controllability and conditioning options.
  • 2.2.9 IGen Fast Models - Optimized models for rapid image generation with reduced latency.
  • 2.2.10 IGen Research Models - Experimental image generation models for research purposes.

2.3 Specialized Model Categories

  • 2.3.1 Stellar v2 Models - Advanced reasoning and analysis models for complex problem-solving.
  • 2.3.2 Audio Generation Models - Models for speech synthesis, music generation, and audio processing.
  • 2.3.3 Video Generation Models - Models for video synthesis, editing, and temporal content creation.
  • 2.3.4 Embedding Models - Models for generating vector representations of text, images, and other data.
  • 2.3.5 Classification Models - Models for content classification, sentiment analysis, and categorization.
  • 2.3.6 Translation Models - Models for language translation and cross-lingual understanding.
  • 2.3.7 Summarization Models - Models specialized for text summarization and content condensation.
  • 2.3.8 Question Answering Models - Models optimized for factual question answering and information retrieval.
  • 2.3.9 Safety Models - Models for content moderation, safety classification, and harm detection.
  • 2.3.10 Evaluation Models - Models for assessing quality, accuracy, and performance of other AI systems.

3. GRANTED PERMISSIONS

3.1 Usage Rights

  • 3.1.1 Use OpenWeight Models for inference, prediction, and output generation.
  • 3.1.2 Deploy models in production environments for commercial and non-commercial purposes.
  • 3.1.3 Integrate models into applications, services, and platforms.
  • 3.1.4 Process proprietary and confidential data through licensed models.
  • 3.1.5 Scale usage according to computational resources and business needs.
  • 3.1.6 Use models across multiple geographic regions and jurisdictions.
  • 3.1.7 Combine multiple TNSA models in integrated solutions.
  • 3.1.8 Use models for both batch processing and real-time inference.
  • 3.1.9 Implement custom inference optimizations and performance enhancements.
  • 3.1.10 Use models in research, development, and experimental applications.

3.2 Modification Rights

  • 3.2.1 Fine-tune models on custom datasets for specialized applications.
  • 3.2.2 Modify model architectures for performance or efficiency improvements.
  • 3.2.3 Quantize, compress, or optimize models for specific hardware platforms.
  • 3.2.4 Merge or ensemble multiple models for enhanced capabilities.
  • 3.2.5 Extract and use individual model components or layers.
  • 3.2.6 Adapt models for different programming languages or frameworks.
  • 3.2.7 Create domain-specific variants through transfer learning.
  • 3.2.8 Implement custom training procedures and optimization techniques.
  • 3.2.9 Modify input/output interfaces and data preprocessing pipelines.
  • 3.2.10 Develop novel applications and use cases based on model capabilities.

3.3 Distribution Rights

  • 3.3.1 Distribute unmodified OpenWeight Models with proper attribution.
  • 3.3.2 Share derivative models created through permitted modifications.
  • 3.3.3 Include models in open-source projects and repositories.
  • 3.3.4 Distribute models through academic and research channels.
  • 3.3.5 Package models with applications and commercial products.
  • 3.3.6 Provide models to customers, partners, and collaborators.
  • 3.3.7 Host models on cloud platforms and model repositories.
  • 3.3.8 Create and distribute model variants for different use cases.
  • 3.3.9 Share models within organizations and affiliated entities.
  • 3.3.10 Contribute models to community projects and initiatives.

4. USAGE RESTRICTIONS

4.1 Prohibited Uses

  • 4.1.1 Using models to generate illegal content or facilitate criminal activities.
  • 4.1.2 Creating deepfakes or synthetic media intended to deceive or harm individuals.
  • 4.1.3 Developing surveillance systems that violate privacy rights or human dignity.
  • 4.1.4 Training models on data obtained without proper consent or legal authorization.
  • 4.1.5 Using models to discriminate against protected groups or individuals.
  • 4.1.6 Generating content that promotes violence, hatred, or extremist ideologies.
  • 4.1.7 Creating systems designed to manipulate democratic processes or elections.
  • 4.1.8 Using models for military weapons development or autonomous weapons systems.
  • 4.1.9 Developing applications that could cause mass harm or societal disruption.
  • 4.1.10 Reverse engineering models to extract proprietary training data or methodologies.

4.2 Technical Restrictions

  • 4.2.1 Removing or obscuring attribution notices, copyright statements, or license information.
  • 4.2.2 Circumventing built-in safety measures, content filters, or usage monitoring.
  • 4.2.3 Attempting to extract or reconstruct training data from model weights.
  • 4.2.4 Using models in ways that exceed specified computational or usage limits.
  • 4.2.5 Modifying models to remove safety guardrails or ethical constraints.
  • 4.2.6 Distributing models without required documentation or safety information.
  • 4.2.7 Using models in safety-critical applications without proper validation.
  • 4.2.8 Combining models with malicious code or harmful software components.
  • 4.2.9 Implementing models in ways that violate applicable privacy regulations.
  • 4.2.10 Using models to create competing AI services that directly replicate TNSA offerings.

4.3 Commercial Restrictions

  • 4.3.1 Certain models may require separate commercial licensing for revenue-generating use.
  • 4.3.2 High-volume commercial usage may be subject to additional terms and fees.
  • 4.3.3 Reselling unmodified models as standalone products is prohibited.
  • 4.3.4 Using TNSA trademarks or branding without explicit permission is forbidden.
  • 4.3.5 Creating derivative works that compete directly with TNSA services may be restricted.

This comprehensive OpenWeight Model Licensing Framework contains 200+ detailed clauses covering all aspects of model usage, modification, and distribution. For specific licensing details:

→ License Overview & Model Catalog (Sections 5-7)→ Attribution Requirements & Compliance (Sections 8-10)