The term “model” is one of those super overloaded terms. Depending on the conversation it can mean:

- a product (most accurate here imo)

- a specific set of weights in a neural net

- a general architecture or family of architectures (BERT models)

So while you could argue this is a “model” in the broadest sense of the term, it’s probably more descriptive to call it a product. Similarly we call LLMs “language” models even if they can do a lot more than that, for example draw images.

> Also, I don't understand the comments about Google being behind in agentic workflows.

It has to do with how the model is RL'd. It's not that Gemini can't be used with various agentic harnesses, like open code or open claw or theoretically even claude code. It's just that the model is trained less effectively to work with those harnesses, so it produces worse results.

There are hints this is a preview to Gemini 3.1.