For me it's 3.4k tok/s of pure nonsense, the model is bad, you tell it it's wrong, it acknowledge it's wrong and repeats the same nonsense. It reminds me my nephew though. Ask it something like: "I want to play the guitar on the surface of the Moon. What speakers do you suggest." and then "But Moon has no atmosphere, how the sound will travel?".

Note that this coding model is trained on programming use cases, and is also not tuned for multi-turn chat.

You can ask it to implement an algorithm; we provide suggested prompts you can test.

Also, this tech preview is really about the speed of the inference engine (not the model itself) so I'm glad you got 3.4k tok/s!

That's what I tested first and the model failed, even after suggestions that it was wrong and how to fix it's errors.