The Best Open-Source Generative AI Models Available Today

Generative AI
Written By Alex Kouchev

Businesses have many reasons to choose open-source over proprietary tools when diving into generative AI. Whether it's due to cost, opportunities for customization and optimization, transparency, or community support, open-source AI models offer significant advantages. However, there are also disadvantages, which I discuss more fully in this article.

Understanding Open-Source AI

In general software terms, open-source means that the source code is publicly available and can be used freely for almost any purpose. For AI models, though, there is debate about what this entails, as we’ll explore while discussing individual models. Let’s dive in.

Stable Diffusion

Stable Diffusion 3 is one of the most powerful and flexible image generation models, and it’s the most widely-used open-source image model. It supports text-to-image and image-to-image generation and is renowned for creating highly realistic and detailed images. Using Stable Diffusion isn’t as straightforward as using commercial tools like ChatGPT. Instead of its own web interface, it’s accessed through third-party tools like DreamStudio and Stable Diffusion Web, or you can compile and run it locally, requiring your own compute resources and technical know-how.

Meta Llama 3

Meta Llama 3 is a family of language models available in various sizes, suitable for applications from lightweight mobile clients to full-size cloud deployments. It powers the Meta AI assistant on Meta’s social media platforms and can be deployed for natural language generation and coding. It runs on relatively low-powered hardware. However, some debate exists on whether it’s truly open-source, as Meta has not disclosed all details of its training data.

Mistral AI

Mistral is a French startup that has developed several generative AI models under open-source licenses, including Mistral 7B, designed to be lightweight and deployable on low-power hardware, and the more powerful Mistral 8x22B. It boasts a strong user community offering support and positions itself as a highly flexible and customizable generative language model.

GPT-2

OpenAI has open-sourced GPT-2, an earlier version of the engines now powering ChatGPT. Although not as big or powerful as GPT-3.5 or GPT-4, GPT-2’s 1.2 billion parameters make it adequate for many language-based tasks, such as text generation or powering chatbots. OpenAI makes GPT-2 available under the MIT license, aligning with open-source principles.

BLOOM

BLOOM is the world’s largest open, multilingual language model, built on 176 billion parameters. Developed by Hugging Face and over 1,000 researchers in a global collaborative project called BigScience, it’s freely available under the project’s Responsible AI License, which restricts harmful uses. Though not technically open-source, BLOOM is a significant experiment in developing and distributing ethical AI.

Grok.AI

Grok.AI, designed by X.ai, claims to be the world’s largest open-source model, though its open-source status is debated. X.ai, founded by Elon Musk, has made the model's weights and architecture public but hasn't disclosed all the code or training data. Unlike models designed specifically for dialogue, Grok is a “mixture of experts” model, reflecting its general-purpose design.

Falcon

Developed by the Technology Innovation Institute in Abu Dhabi, the Falcon models—Falcon 40B and Falcon 180B—are freely available. The smaller model is released under the Apache 2.0 license, while the larger model has some usage and distribution conditions. Both models rank highly on performance leaderboards, just below GPT-4.

Conclusion

This exploration of open-source generative AI tools highlights the diverse options available and underscores the transformative potential these technologies hold for businesses eager to leverage AI's power while embracing transparency, cost-efficiency, and robust community support.

About Alex Kouchev

🚀 Workspace Innovator: I review AI impact on Work | Connecting HR and Tech | 12+ Years Leading People & Product Initiatives | opinions expressed are my own.

For over a decade, guided by the principle that "People Are People, Not Human Resources,"
I've immersed myself in the evolving landscape of work trends, HR technology, and organizational dynamics.

My mission is clear: to ensure that in the age of AI and Digital Transformation, we create workplaces where human intelligence and machine capabilities harmoniously co-exist. I focus on designing ethical, innovative solutions that not only drive organizational performance but also elevate the work experience for every associate.

With over 12 years of experience in International HR and Product Management, I’ve pioneered the development of human-centric solutions that deliver organizational efficiencies and boost employee satisfaction. My unique background empowers me to bridge the gap between functional and technical stakeholders, thus accelerating digital transformation across the enterprise.

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