For whatever reason, the Chinese companies tend to go with very permissive licensing, while Cohere, Mistral, Meta (Llama), and some others add really weird commercial restrictions (though this trend may be reversing). IBM Granite is actually Apache 2.0 and way more “open” and documented than even the Chinese tech companies, but unfortunately their models are “small” (3B) and not very cutting edge.
Another note: Huggingface Transformers (Also Apache 2.0, and from a US company) is the reference code to run open models, but there are many other implementations to choose from (exllama, mlc-llm, vllm, llama.cpp, internlm, lorax, Text Generation Inference, Apple MLX, just to name a few).
How do you Apache license a LLM? Do they just treat the weights as code?
It’s software, so yeah, I suppose. See for yourself: https://huggingface.co/Qwen/QwQ-32B-Preview
Deepseek chose MIT: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
For whatever reason, the Chinese companies tend to go with very permissive licensing, while Cohere, Mistral, Meta (Llama), and some others add really weird commercial restrictions (though this trend may be reversing). IBM Granite is actually Apache 2.0 and way more “open” and documented than even the Chinese tech companies, but unfortunately their models are “small” (3B) and not very cutting edge.
Another note: Huggingface Transformers (Also Apache 2.0, and from a US company) is the reference code to run open models, but there are many other implementations to choose from (exllama, mlc-llm, vllm, llama.cpp, internlm, lorax, Text Generation Inference, Apple MLX, just to name a few).