Legal & Licensing Guide
Open Source vs. Open Weights in Artificial Intelligence
The legal and practical distinctions between genuine Open Source software and Open-Weight models with commercial restrictions, usage limits, and distillation clauses.
Top Open Weights & Open Source Models License Comparison
Compare commercial use, user caps, synthetic data rules, and OSI compliance at a glance.
| Model & Publisher | License Name | Commercial Use | User Cap / Limits | Dataset Released? | Train Competing Models? |
|---|---|---|---|---|---|
DeepSeek-V3 / R1 DeepSeek AI | MIT License Permissive License | Full Commercial Completely permissive. No user threshold or synthetic data restrictions. | No user limit | Private | Allowed |
Llama 3.1 / 3.2 / 3.3 Meta AI | Llama 3.3 Community License Custom Open Weights | Conditional Free for standard business, but cannot use outputs to train non-Llama models. | > 700M monthly active users requires custom license | Private | Restricted |
Llama 4 Scout / Maverick Meta AI | Llama 4 Community License Custom Open Weights | Conditional MoE multimodal models. Same community license structure as Llama 3 — no output-based training of competing models. | > 700M MAU requires Meta's separate commercial agreement | Private | Restricted |
Meta Muse Glimmer 30B Meta Superintelligence Labs | Apache 2.0 Permissive License | Full Commercial Full Apache 2.0. Distilled from Muse Spark — no use restrictions beyond the open license. | No user limit | Private | Allowed |
Qwen3 (0.6B to 32B dense) Alibaba Cloud / Qwen Team | Apache 2.0 Permissive License | Full Commercial All dense Qwen3 sizes are Apache 2.0. Full commercial freedom including fine-tuning and redistribution. | No user limit | Private | Allowed |
Qwen3 235B-A22B (MoE) Alibaba Cloud / Qwen Team | Apache 2.0 Permissive License | Full Commercial Apache 2.0. MoE flagship. 22B active params. Requires >100M MAU to be reviewed by Alibaba for certain commercial uses. | Notify Alibaba Cloud for deployments >100M MAU | Private | Allowed |
Qwen 2.5 (0.5B to 72B) Alibaba Cloud | Apache 2.0 (most sizes) / Tongyi Permissive License | Full Commercial Apache 2.0 for 0.5B to 32B models. Full commercial freedom. | > 100M MAU for certain 72B variants | Private | Allowed |
OLMo 2 (7B / 13B) Allen Institute for AI (Ai2) | Apache 2.0 (Code, Weights & Dolma Data) Permissive License | Full Commercial 100% OSI-compliant Open Source AI: weights, code, and full Dolma dataset released. | No user limit | Full Data (Dolma) | Allowed |
Gemma 3 (4B / 12B / 27B) Google DeepMind | Gemma Terms of Use Custom Open Weights | Conditional Multimodal open weights. Google acceptable-use policy restricts harmful content, competitive distillation, and misrepresentation. | No user limit | Private | Restricted |
Mistral NeMo / 7B v0.3 Mistral AI | Apache 2.0 Permissive License | Full Commercial Permissive Apache 2.0. Note that Mistral Large uses proprietary licensing. | No user limit | Private | Allowed |
Xiaomi MiMo V2.6 (Flash / Pro) Xiaomi AI | Apache 2.0 Permissive License | Full Commercial Apache 2.0. MoE omnimodal models (text, image, video, audio). Full commercial use permitted. | No user limit | Private | Allowed |
Phi-4 (14B) Microsoft | MIT License Permissive License | Full Commercial Standard MIT open software license. | No user limit | Private | Allowed |
1. What True Open Source AI Actually Means (The OSI Definition)
According to the Open Source Initiative (OSI), true Open Source AI requires full transparency across the entire machine learning pipeline: source code, training datasets, data preprocessing scripts, and training hyperparameters. Merely releasing model weights does not qualify as open source.
2. Open Weights: Why Llama, Mistral & Qwen Are Not Strictly Open Source
Models like Meta Llama 3, Mistral Commercial, and certain frontier releases are Open Weights, not open source. The model weights are publicly downloadable, but training data remains proprietary and usage is governed by bespoke license agreements with legal restrictions.
3. Commercial Usage Caps & The 700M Active User Rule
The Meta Llama 3 Community License requires companies with more than 700 million monthly active users to apply for a separate commercial license from Meta. While irrelevant for startups, this is a critical consideration for enterprise compliance and future-proofing.
4. The Synthetic Data Distillation Trap
Most proprietary and open-weight licenses (including Llama 3) explicitly prohibit using model outputs to train or improve competing language models. If you plan to distill a large model into a smaller task-specific model, verify whether your model license permits synthetic data training (e.g. Apache 2.0 models like OLMo or MIT models like DeepSeek).
Frequently Asked Questions
No. Llama 3 is an open-weights model published under the Meta Llama 3 Community License. Because it imposes commercial user thresholds (700M MAU) and restricts using outputs to train other models, it does not conform to the OSI Open Source definition.
DeepSeek models (V3, R1) are released under the highly permissive MIT License. Allen AI OLMo is licensed under Apache 2.0 with open datasets. Falcon models are licensed under Apache 2.0.
Under Apache 2.0 and MIT licenses, yes, without restriction. Under Llama 3 Community License, yes, provided your company does not exceed 700M monthly active users across all products and adheres to acceptable use policies.
You cannot legally use that model's outputs to fine-tune or pretrain a competing foundation model. Violating this clause can invalidate your commercial rights and expose your company to intellectual property disputes.
OSI-approved licenses (like Apache 2.0 or MIT) have decades of established case law and predictable legal precedent. Custom community licenses introduce novel ambiguity around derivative works and liability.
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