Your AI bill tripled last quarter. Your CTO forwarded you an article about companies saving 70% by switching to open models. Now someone is asking you to figure out what that would actually look like.
I spent the last few weeks digging into this. The numbers, the hardware, the real trade-offs. Here's what I found, with enough specifics that you can actually make a decision rather than just nodding along to another "open source is the future" think piece.
What "Open Models" Actually Means
When someone says "open model" they mean an AI model where the weights (the learned parameters that make the model work) are publicly downloadable. You grab the file, run it on your hardware, and you don't pay anyone per request.
The big names right now: Meta's Llama 4, DeepSeek V4, Zhipu's GLM-5.2, Moonshot's Kimi K3, Alibaba's Qwen 3.5, and Google's Gemma 4.






