Open-source models make their code and model weights public, allowing anyone to examine, alter, or set loose in the world. Closed-source models, on the other hand, are commercial products whose insides are kept secret and whose outside is accessible only through commercial portals.
For instance, GPT-4.5 from OpenAI is a closed model, branding itself as OpenAI's largest and most proficient chat AI to date. Yet, the particulars of how GPT-4.5 operates are a closely held secret. Using it necessitates subscribing to a paid API. In sharp contrast, LLaMA 3 from Meta is open-source, enabling anyone with an internet connection to access the model and evaluate its performance. Wide adoption, of course, requires not just access but also a model that can do useful things. (Usefulness is somewhat subjective, but in this context, it generally means providing informative and coherent outputs.)
Advantages of Open-Source vs Closed-Source
Benefits of Open Source: Being cost-effective (incurs no API fees) and highly customizable via fine-tuning. These models are also quite transparent (anyone can inspect for biases), and they benefit from widespread community contributions. You can maintain full control over your data by deploying these models on your own infrastructure.
Benefits of Closed Source: Top-class, ready-to-use performance. They often set the standard for the industry. These models give you easy APIs, strong documentation, and support you'd expect from enterprises. They also come integrated with robust security and compliance features.
A Shifting Landscape in 2025
At LlamaCon 2025, Meta highlighted this trend by placing its open-source LLaMA models in direct competition with the closed ecosystem of OpenAI. It even introduced a Llama API to give developers full control and no vendor lock-in.
This demonstrates clearly that open-source platforms can now engage in direct competition with proprietary platforms. And many companies are starting to adopt open models, which are now rivaling closed systems in performance.
Conclusion
The 2025 artificial intelligence picture is a picturesque pansy of open and closed models. Closed-source leaders still provide top-tier performance and support, but open-source alternatives are rapidly catching up, with more flexible, cost-efficient, and transparent models. The best choice depends on your specific needs, whether you prioritize customization and community collaboration, or prefer a no-hassle solution with vendor support.
