Enterprise LLMs: Comparing Leading Models

The LLM Race: Not All Models are Built Equal

Enterprises are becoming more AI-driven by the hour. Meanwhile, large language model (LLM) innovations are speeding ahead, with leaders jostling for LLM supremacy.

Such intense competition leads to exciting benefits for enterprises. But attaining those benefits can lead to growing pains, not only in response to fast-and-furious innovation, but also because of model quirks.

As enterprises rush to adopt these models, understanding the intricacies of licensing is crucial. Not all models are freely available for commercial use, and each comes with unique licensing terms. Those terms may impose restrictions on how the model is used, modified, or redistributed. 

In this guide, we map out the licensing landscape for several prominent LLM families. That way, you can better compare their quirks and restrictions, helping you choose the best model for your business needs.

Understanding Licensing & What It Means for You

Let’s review how licenses dictate what you can and can’t do with leading LLMs. 

Each model license defines permissions for use, distribution, and modification. Some models come with open-source licenses, while others have proprietary terms that can restrict usage for commercial purposes.

The following table outlines several leading LLMs, their licensing terms, what they allow and restrict, and any notable quirks that could impact your decision.

A Closer Look at the Leaders

1. Llama3.1 Family – Meta’s RAIL License

The Llama3.1 family is part of Meta’s open-source initiative. It falls under the Responsible AI License (RAIL), which is designed to ensure ethical AI use, including behavioural-use restrictions. This license allows for commercial use, but comes with significant restrictions, especially for sensitive industries like military, law enforcement, and surveillance. 

The Llama3.1 models are designed with strong ethical use cases in mind. This ensures they can’t be exploited for harmful applications. One key limitation of these models is that any fine-tuning or modification of the model must also follow ethical guidelines.

💡 Takeaway: Llama3.1 is a powerful choice for businesses prioritizing responsible AI deployment.

2. Gemma Family – Apache 2.0 License

Gemma models are licensed under the widely-used Apache 2.0, which allows for commercial use, redistribution, and modification with minimal restrictions, provided attribution is given to the original authors. 

One standout feature of the Gemma family is its optimization for cost-effective deployment in large-scale systems. However, it’s important to note that the license forbids the use of any related trademarks without explicit permission.

💡 Takeaway: Gemma offers flexibility for enterprise-level applications, particularly in scalable environments.

3. Mixtral Family – Apache 2.0 License

The Mixtral family is also released under the Apache 2.0 license, allowing businesses to freely use, modify, and distribute the models with attribution. The models are known for their lightweight architecture, making them an excellent choice for rapid inference tasks in resource-constrained environments. 

Mixtral is a go-to model for organizations looking to deploy LLMs with minimal hardware overhead.

Newer Mixtral models like Mixtral 8x7B and 8x22B use a sparse mixture-of-experts (SMoE) architecture for high efficiency and fast inference making it particularly well suited for multilingual tasks.

💡 Takeaway: Mixtral is ideal for businesses needing quick deployment of LLMs with lower infrastructure costs.

4. Falcon Family – Apache 2.0 License

The Falcon models are licensed under the Apache 2.0 license, allowing commercial use as long as credit is given. Newer Falcon models like Falcon 180B have a modified license, which includes restrictions like limitations related to hosting and commercial usage

Falcon models are praised for their multilingual capabilities and are often chosen for niche applications that require support for less commonly spoken languages.

💡 Takeaway: Falcon shines in multilingual settings but comes with content-related restrictions that may limit some applications.

5. Snowflake Arctic – Apache 2.0 License

Snowflake Arctic is released under the Apache 2.0 license, allowing businesses to use, modify, and redistribute it with proper attribution. It offers flexible deployment options for enterprise-grade AI, excelling in scalable and efficient AI solutions. 

The Snowflake model family is well-suited for industries requiring robust AI deployment like large-scale enterprise applications​

💡 Takeaway: Snowflake Arctic stands out as a scalable and flexible solution, making it a strong candidate for industries requiring robust, large-scale AI deployments.

Choosing the Right Model for Your Business

Selecting the right LLM for your business will ultimately depend on factors like budget, use case, and legal requirements. 

If you’re looking for a versatile, open model for rapid deployment, Mixtral or Gemma may be the best fit. If your use case involves strict ethical guidelines or niche language processing, Llama3.1 or Falcon could make more sense. For organizations willing to invest in specialized capabilities, Snowflake Arctic offers unrivaled performance in specific regions.

By better understanding these licensing terms and quirks, you’ll be able to make more informed decisions that comply with legal standards — allowing you to fully leverage LLMs in increasingly innovative ways.

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