Open-weight models are not the same as open source: their weights are visible but the training data and creation process remain hidden, and their licenses vary dramatically from permissive (MIT for DeepSeek) to restrictive (Meta Llama's caps and competitor restrictions).
CJ distinguishes open-weight from open source, explaining that you can see the internal numbers but not how they were produced, then contrasts the MIT license used by DeepSeek (allowing anyone to profit) with Meta Llama's restrictive license. ✦ AI generated
CJ · Syntax · 2026-07-30 · original ↗
starts at this moment · 14:10
When an AI lab makes their model freely available for people to download and use, we call this open weight because we can actually look inside the model file and see all of those numbers or weights. And this is where we can make a clear distinction between open weight and open source. Now, open source is a term that comes from the world of software. It's how we license open source software. But the main difference here is that we can see the weights, the numbers inside of that model file, but we can't actually see how that model was created or what data was used or what actually encoded all of those weight values inside of the file. Now, what you actually do with that model file itself is also under a license and sometimes a terms of service. And that's where this is closer to open source software. And in this scenario, models have a license or a terms of service, sometimes even an open source license that dictate what can be done with their models once you've downloaded them. For instance, DeepSeek models are released under the MIT license. And this means that anyone is allowed to download, run, and even profit from their models. So, as a US citizen, you could start your own AI company that basically just runs fine-tuned or tweaked DeepSeek models. You don't even have to have an AI lab or billions of dollars. You just need to rent the infrastructure and now you've got a business selling custom access to custom AI models. But in contrast to that, there are models like Llama from Meta that have a license which cap free commercial use at 700 million monthly active users and a competitor restriction clause that blocks entire industries. So while these llama models are open weight, we can see all of the weights inside of them. We can't necessarily start a really large business using them. And if we work in certain industries, we're not really supposed to use those models either because that would be violating their terms of service.
verbatim transcript · starts at 14:10
14:10a file. It's a file that has trillions or billions of numbers inside of it. And when an AI lab makes their model freely available for people to download and use, we call this open weight because we can actually look inside the model file and see all of those numbers or weights. And this is where we can make a clear distinction between open weight and open source. Now, open source is a term that
14:31comes from the world of software. It's how we license open source software. But the main difference here is that we can see the weights, the numbers inside of that model file, but we can't actually see how that model was created or what data was used or what actually encoded all of those weight values inside of the file. Now, what you actually do with that model file itself is also under a
14:54license and sometimes a terms of service. And that's where this is closer to open source software. And in this scenario, models have a license or a terms of service. sometimes even an open- source license that dictate what can be done with their models once you've downloaded them. For instance, DeepSeek models are released under the MIT license. And this means that anyone is allowed to download, run, and even
15:16profit from their models. So, as a US citizen, you could start your own AI company that basically just runs fine-tuned or tweaked DeepSeek models. You don't even have to have an AI lab or billions of dollars. You just need to rent the infrastructure and now you've got a business selling custom access to custom AI models. But in contrast to that, there are models like Llama from Meta that have a license which cap free
15:40commercial use at 700 million monthly active users and a competitor restriction clause that blocks entire industries. So while these llama models are open weight, we can see all of the weights inside of them. We can't necessarily start a really large business using them. And if we work in certain industries, we're not really supposed to use those models either because that would be violating their terms of service. Now, the other thing
16:03to think about is even though these openweight models are free to download, they're not necessarily free to run. Models require hardware and electricity to run. And the scale of openweight models varies drastically. There are some openweight models that can run on your phone, and that usually means they're 1 billion parameters or weights or less. Then there are some models that require massive servers with dozens or hundreds
16:27of GPUs to run. And typically those are models with trillions of parameters. And typically the size of the model indicates how well it performs. And so this is where we get to the recent news. If you look at the models released by Moonshot AI with Kimmy or Alibaba Cloud with Quinn, those models have over two trillion parameters. And it's been shown that these models are just as good, if