Comparison
Inference vs TPU
Inference and TPU are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Inference
Inference comes up when the question is fundamentally about inference.
A ChatGPT response: one inference call per turn.
When you would reach for TPU
TPU comes up when the question is fundamentally about infrastructure.
Gemini trained on TPU v5p pods.
Frequently asked
What is the difference between Inference and TPU?
Inference: Inference is what happens when you actually run a trained model on new input. For LLMs that means generating tokens one at a time, with sampling and a KV cache. TPU: TPUs are Google's custom AI accelerators, designed specifically for the matrix and reduction operations of neural networks. Used to train Gemini and large parts of Google's AI stack.
When should I use Inference vs TPU?
Inference is the right concept when you are focused on inference. TPU applies when you are focused on infrastructure.
Are Inference and TPU the same thing?
No. Inference is inference; TPU is infrastructure. They are related but address different parts of the AI stack.