What’s The Difference Between Open Weight And Open Source AI?

Open source has been a known phrase for years now in tech – even long before ChatGPT and the current AI race. Even back then, developers were building software in the open, sharing code and improving each other’s work. Now a different phrase keeps coming up in company announcements or funding news: open weight. It sounds close enough to make many people think the two mean the same thing, but they refer to different things, and knowing where they part ways makes it much easier to understand what AI companies are actually releasing.

OpenAI has released open weight AI models, startups have secured billions of dollars around products built for open weight models, and developers are spending more time talking about running AI on their own systems. As a result, two phrases which sound almost identical now have very different meanings.

What Does Open Source Actually Mean?

Open source means the software’s code is available for people to inspect, modify and build upon. Developers can see how everything works, make improvements and even adapt the software for their own projects, depending on the licence.

SpaceXAI recently announced Grok Build is now open source and explained why it made the decision. The company said, “Publishing the code is the most direct way to build toward a robust and reliable harness. You can read the source to see exactly how it works, from context assembly to tool call dispatch.”

It also explained why opening the code benefits developers, saying, “Open sourcing also makes the harness easier to explore and extend: if you’re working with skills, plugins, hooks, MCP servers, or subagents, the source is the definitive reference for how each is loaded and invoked.”

Basically, open source gives developers access to the software itself. They can inspect the code, understand how it works and, if the licence allows, adapt it for their own needs.

What Makes Open Weight Different?

Open weight does not mean every piece of software used to build an AI model becomes available. Instead, developers receive the trained model, which they can download, run on their own infrastructure and customise for their own work.

OpenAI explained this when it announced its latest open weight models last August. The company said, “These are our most advanced open weight reasoning models, which can handle advanced problem solving and are adaptable to many tasks. They give anyone, from individual developers and local nonprofits, to large enterprises and governments, the freedom to run and customize AI on their own infrastructure, democratizing access to AI across industries, communities, and countries globally.”

OpenAI also addressed the whole thing around open source and open weight in its submission to the White House Office of Science and Technology Policy, writing, “We believe the question of whether AI should be open or closed source is a false choice. We need both, and they can work in a complementary way that encourages the building of AI on American rails.”

Those comments explain why many companies now prefer saying open weight. Developers receive the trained model and can build on top of it, although the code, training data and everything used to produce the model may not be available.
 

Why Are Companies Investing So Much In Open Weight?

A lot of the money flowing into AI startups today is going towards businesses built around open weight models. According to Forbes, Fireworks announced a $1.505 billion Series D funding round at a $17.5 billion valuation during July, Together AI secured $800 million, and Baseten also raised around $1.5 billion within the space of only a few weeks.

None of those companies build their own frontier foundation models. Their business is helping customers run, customise and serve open weight models without needing to manage powerful AI hardware themselves.

Forbes explains why simply downloading an open weight model is only the beginning. Running one for customers also requires continuous batching, cache management, quantisation, autoscaling, latency guarantees, monitoring and billing systems. Those services are what these companies sell.

Fireworks said more than 95% of the tokens it serves come from models specialised using customer data, including fine tuned models, adapters, distillations and customer trained models. Forbes said this shows demand for AI systems customised around a company’s own information, such as insurance claims or customer support records.

Can Open Source And Open Weight Exist Together?

Many believe both open source and weight can exist together, but people are debating on how open AI should become.

TechCrunch reported the debate began to heat up after Chinese AI lab Moonshot released Kimi K3, one of the largest open weight language models available. Dean W. Ball, OpenAI’s Head of Strategic Futures, initially argued open weight models could discourage investment in frontier AI labs before withdrawing those comments.

Many people working in AI defended open models. Braden Hancock, co founder of Snorkel AI and a research partner at the Laude Institute, told TechCrunch, “Strong, frontier caliber open source models will place a squeeze on the margins and will bring down the prices of the frontier companies. It will not necessarily mean that the amount of AI usage goes down a little bit. You know, obviously, quite the opposite.”

Clem Delangue, chief executive of Hugging Face, also supported open models, saying, “Restricting open models wouldn’t make AI safer. It would simply hide the risks, concentrate power in the hands of a few and make it harder for the next generation of builders, researchers, academia, non profits, governments to participate in making AI safer and more beneficial for all.”