Google Gemini API Review: Is It The Right Large Language Models (LLMs) For Your Team?

Running a model over a large collection of inputs as a scheduled or queued job instead of one request at a time. Since results are not neede…

Code generation produces source code from a higher-level input such as a natural language description, a specification, or an existing schem…

The context window is how much text, code or other input the model can hold in one request, counted in tokens, together with everything it h…

An embedding model converts text, images, or other content into a list of numbers — a vector — positioned so that items with similar meaning…

Fine-tuning continues training a published model on your own labelled examples, so it adopts a format, a house style or a narrow task withou…

A language model is given descriptions of the functions or tools available to it and, when a request needs one, returns a structured call na…

The model accepts more than text in a single request: images, audio, video frames or documents alongside the prompt. Pricing is usually sep…

Storing the processed form of a prompt's repeated content, such as a long system instruction or a reference document, so that it does not ha…

The vendor prints a rate per million tokens on its own site, separately for the tokens a request reads and the tokens the model writes, so t…

The model can be asked to work through a problem step by step before answering, spending extra generated tokens on the working rather than t…

An interface that returns a model's output incrementally as it is produced, rather than waiting for the full response and sending it in one…