Delete Deployment

BearerAuth

Fireworks AI Docs

Start building with open source AI models

Introduction

Fireworks AI Developer Platform

Get started in minutes with an OpenAI compatible endpoint

Quickstart

This document outlines basic Fireworks AI concepts.

Concepts

A quick guide to navigating and building with the Fireworks platform.

Onboarding

Querying text models

Querying vision-language models

Querying embedding models

Using function-calling

Using grammar mode

Using JSON mode

Overview

Uploading a custom model

Fine-tuning models

A guide for downloading base models, merging them with LoRA adapters, and deploying the result using Fireworks.

Merging LoRA adapters with base models

Understand the performance impact of LoRA fine-tuning, optimization strategies, and deployment considerations.

Understanding LoRA performance

Deploying models

Quantization

On-demand deployments

Fireworks runs a global fleet of hardware on which you can deploy your models.

Regions

Reserved capacity

Direct routing enables enterprise users reduce latency to their deployments.

Direct routing

Rate limits, spend limits and quotas for serverless inference and on-demand deployments

Rate limits, spend limits and quotas

Add and delete additional users in your Fireworks account

Managing users

Set up custom Single Sign-On (SSO) authentication for Fireworks AI

Custom SSO

Data privacy & security

Creates a model response for the given chat conversation.

Create Chat Completion

Creates a completion for the provided prompt and parameters.

Create Completion

Create embeddings

Generate an image

Streaming Transcription

Transcribe audio

Translate audio

Get Account

List Deployments

Get Deployment

Create Deployment

Update Deployment

CRUD APIs for deployed models.

List Models

Get Model

Create Model

Update Model

Delete Model

Get Model Upload Endpoint

Get Model Download Endpoint

Validate Model Upload

List Supervised Fine-tuning Jobs

Get Supervised Fine-tuning Job

Create Supervised Fine-tuning Job

Delete Supervised Fine-tuning Job

List Users

Get User

Create User

Update User

List Datasets

Get Dataset

Create Dataset

Provides a streamlined way to upload a dataset file in a single API request. This path can handle file sizes up to 150Mb. For larger file sizes use [Get Dataset Upload Endpoint](get-dataset-upload-endpoint).


Upload Dataset Files

Get Dataset Upload Endpoint

Validate Dataset Upload

Update Dataset

Delete Dataset

List API Keys

Create API Key

Delete API Key

List Batch Jobs

Get Batch Job

Create Batch Job

Update Batch Job

Cancels an existing batch job if it is queued, pending, or running.

Cancel Batch Job

Get Batch Job Logs

Delete Batch Job

Batch Delete Batch Jobs

List Clusters

Get Cluster

Create Cluster

Update Cluster

Delete Cluster

Retrieve connection settings for the cluster to be put in kubeconfig

Get Cluster Connection Info

List Environments

Create Environment

Get Environment

Update Environment

Connects the environment to a node pool.
Returns an error if there is an existing pending connection.

Connect Environment

Disconnects the environment from the node pool. Returns an error
if the environment is not connected to a node pool.

Disconnect Environment

Delete Environment

Batch Delete Environments

List Node Pools

Get Node Pool

Create Node Pool

Update Node Pool

Get Node Pool Stats

Delete Node Pool

Batch Delete Node Pools

List Node Pool Bindings

Create Node Pool Binding

Delete Node Pool Binding

List Snapshots

Get Snapshot

Create Snapshot

Delete Snapshot

List Aws Iam Role Bindings

Create Aws Iam Role Binding

Delete Aws Iam Role Binding

Start here

Step-by-step guides for hands-on exploration, ideal for interactive learning of AI techniques.

Build with Fireworks

Creative user-contributed projects that showcase innovative applications of Fireworks in diverse contexts.

Community showcase

Learn about the Fireworks Developer Partners Program, including goals, application process, and benefits for tools and platforms in the LLMOps/Gen-Ops ecosystem.

About Fireworks developer partners

Access information, blog posts, FAQs, and detailed documentation for DeepSeek v3 and R1.

DeepSeek Resources

Community

Blog

API Reference

API Reference DLDE

Cookbook

Tools & SDK

Integrations

DeepSeek

Get Started

Status

Support

Prompt caching

Use Predicted Outputs to boost output generation speeds for editing / rewriting use cases

Using Predicted Outputs

Using Document Inlining

This page lists common error codes encountered during inference requests using the Fireworks API, their meanings, and potential resolutions.

Inference errors

Learn to create, deploy, and manage resources using Firectl

Getting Started

Authentication for access to your account

Authentication

List various resources in an Fireworks AI account

List Resources

Create a Deployment on Fireworks AI platform

Create a deployment

Create a fine-tuning job with a base model

Create a fine-tuning job

Create a Dataset on Fireworks AI platform

Create a Dataset

Deletes resource(s) in a Fireworks AI account

Delete Resources

Deploy Model

Download a model from third-party locations

Download a model

Retrieves model information from Fireworks AI platform

Get Resources

Imports specified model from Fireworks AI Platform

Import Model

Undeploy a model on Fireworks AI platform

Undeploy Model

Updates Resources on Fireworks AI platform

API Documentation

LLM API

Embeddings API

Image API

Audio API

Accounts

Deployments

Deployed Models

Models

Supervised Fine Tuning Jobs

Users

Datasets

API Keys

Delete Deployment

Authorizations

Path Parameters

Query Parameters

Response