> ## Documentation Index > Fetch the complete documentation index at: https://docs.bespokelabs.ai/llms.txt > Use this file to discover all available pages before exploring further. # Nimble > Every Nimble model answers at one endpoint, with probabilities. Nimble is a family of models from Bespoke Labs. Every Nimble model answers with probabilities, so you can set your own thresholds. You call every model at the same endpoint, `POST https://api.bespokelabs.ai/v1/systemone`. The `model` field in the request picks the model. | Model | What it does | Guide | | - | - | - | | `nimble-latest`, `nimble-v3` | Answers up to 64 typed questions about a piece of text or JSON. | [Question types](/nimble/questions) | | `nimble-factcheck-lite`, `nimble-factcheck`, `nimble-factcheck-max` | Checks whether a document supports each claim in a list. | [Fact check](/nimble/factcheck) | | `nimble-codegrep-lite`, `nimble-codegrep`, `nimble-codegrep-max` | Scores which files and folders a coding agent needs for a query. | [Code search](/nimble/codegrep) | `nimble-latest` is the newest general Nimble model, which is `nimble-v3` now. Use `nimble-latest` to get each new model when it comes out. Use `nimble-v3` to stay on this model. `bespokelabs/Bespoke-Nimble-9B-v3` is another name for `nimble-v3`. The previous model is still available as `bespokelabs/Bespoke-Nimble-9B`. Fact check and code search each come in three sizes: * The `-lite` model is the fastest and the cheapest. A small model answers every question. * The model with no suffix, e.g., `nimble-factcheck`, is in between. The small model answers every question first. Then a larger model answers again the questions that the small model is unsure about. * The `-max` model is the most accurate and costs the most. It uses the largest models. ## The request format Every model takes the same request format, which is called System One. A request has three fields: * `model` names the model. * `state` is the text or JSON to ask about. * `questions` maps your own question IDs to questions. The answers use the same IDs. You can send the requests with plain HTTP. You can also use the `bespokelabs` Python SDK or TypeSafe's Python SDK. The path `/v1/nimble/systemone` takes the same requests as `/v1/systemone`. The `bespokelabs` SDK uses that path. The general models have three types of question: * A `noul` question asks whether a statement is true. The answer is the probability that it is true. * A `choice` question asks which of 2 to 255 options fits best. The answer names the most likely option and gives the probability of every option. * A `score` question asks where the state falls on a scale of 2 to 255 ordered levels. The answer is the expected level. Fact check takes only `noul` questions. Code search takes `noul` questions, and it also accepts `boolean` questions, which it answers the same way. Get a key and make your first request. Write `noul`, `choice`, and `score` questions and read the answers. What each model costs and how Nimble counts tokens. The full request and response format.