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I often like to think about https://github.com/chrislgarry/Apollo-11 as an analogy. It's public domain with available source, in the assembly language in which it was written... so it fills all the definitions of OSS!
But the process by which that code arose, the ability to modify any line and understand its impact (heh) on a real execution environment, is dependent on a massive process that required billions of dollars and thousands of the smartest people on the planet. For all intents and purposes, without that environment, it is as reliably modifiable as an executable binary in any other context - or a set of weights, in this one!
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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I don't think that's a great example.
For instance, I can step through and even modify that code using tooling like AGC emulators like this one http://www.ibiblio.org/apollo/#gsc.tab=0
What makes it open source is access to the same level of source access that the original developers worked in.
That's what's missing here. Mistral's engineers do not simply open this binary in their editor to do their job.
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ollama
Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
The authors don't seem to care about the principle of least privilege: https://github.com/ollama/ollama/issues/851#issuecomment-177...
It makes me wonder what other security issues they might now care about.
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FYI, vLLM also just added experiment multi-lora support: https://github.com/vllm-project/vllm/releases/tag/v0.3.0
Also check out the new prefix caching, I see huge potential for batch processing purposes there!
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You can either modify the model weights in a way that doesn't cause any real differences (change a few bits somewhere should be enough), or you could watermark the actual text output.
Here's a list of research for watermarking LLMs.
https://github.com/hzy312/Awesome-LLM-Watermark?tab=readme-o...
