# Fireworks AI Docs

## Docs

- [Exporting Billing Metrics](https://docs.fireworks.ai/accounts/exporting-billing-metrics.md): Export billing and usage metrics for all Fireworks services
- [Service Accounts](https://docs.fireworks.ai/accounts/service-accounts.md): How to manage and use service accounts in Fireworks
- [Custom SSO](https://docs.fireworks.ai/accounts/sso.md): Set up custom Single Sign-On (SSO) authentication for Fireworks AI
- [Managing users](https://docs.fireworks.ai/accounts/users.md): Add, delete, and manage roles for users in your Fireworks account
- [Create a Message](https://docs.fireworks.ai/api-reference/anthropic-messages.md): **Anthropic-compatible endpoint.**
- [Streaming Transcription](https://docs.fireworks.ai/api-reference/audio-streaming-transcriptions.md)
- [Transcribe audio](https://docs.fireworks.ai/api-reference/audio-transcriptions.md)
- [Translate audio](https://docs.fireworks.ai/api-reference/audio-translations.md)
- [Cancel Reinforcement Fine-tuning Job](https://docs.fireworks.ai/api-reference/cancel-reinforcement-fine-tuning-job.md)
- [Create API Key](https://docs.fireworks.ai/api-reference/create-api-key.md)
- [Create Batch Inference Job](https://docs.fireworks.ai/api-reference/create-batch-inference-job.md)
- [Create Batch Request](https://docs.fireworks.ai/api-reference/create-batch-request.md)
- [Create Dataset](https://docs.fireworks.ai/api-reference/create-dataset.md)
- [Load LoRA](https://docs.fireworks.ai/api-reference/create-deployed-model.md)
- [Create Deployment](https://docs.fireworks.ai/api-reference/create-deployment.md)
- [Create dpo job](https://docs.fireworks.ai/api-reference/create-dpo-job.md)
- [Create Evaluation Job](https://docs.fireworks.ai/api-reference/create-evaluation-job.md)
- [Create Evaluator](https://docs.fireworks.ai/api-reference/create-evaluator.md): Creates a custom evaluator for scoring model outputs. Evaluators use the [Eval Protocol](https://evalprotocol.io) to define test cases, run model inference, and score responses. They are used with evaluation jobs and Reinforcement Fine-Tuning (RFT).
- [Create Model](https://docs.fireworks.ai/api-reference/create-model.md)
- [Create Reinforcement Fine-tuning Job](https://docs.fireworks.ai/api-reference/create-reinforcement-fine-tuning-job.md)
- [Create Reinforcement Fine-tuning Step](https://docs.fireworks.ai/api-reference/create-reinforcement-fine-tuning-step.md)
- [Create secret](https://docs.fireworks.ai/api-reference/create-secret.md)
- [Create Supervised Fine-tuning Job](https://docs.fireworks.ai/api-reference/create-supervised-fine-tuning-job.md)
- [Create User](https://docs.fireworks.ai/api-reference/create-user.md)
- [Create embeddings](https://docs.fireworks.ai/api-reference/creates-an-embedding-vector-representing-the-input-text.md)
- [Delete API Key](https://docs.fireworks.ai/api-reference/delete-api-key.md)
- [Delete Batch Inference Job](https://docs.fireworks.ai/api-reference/delete-batch-inference-job.md)
- [Delete Dataset](https://docs.fireworks.ai/api-reference/delete-dataset.md)
- [Unload LoRA](https://docs.fireworks.ai/api-reference/delete-deployed-model.md)
- [Delete Deployment](https://docs.fireworks.ai/api-reference/delete-deployment.md)
- [Delete dpo job](https://docs.fireworks.ai/api-reference/delete-dpo-job.md)
- [Delete Evaluation Job](https://docs.fireworks.ai/api-reference/delete-evaluation-job.md)
- [Delete Evaluator](https://docs.fireworks.ai/api-reference/delete-evaluator.md): Deletes an evaluator and its associated versions and build artifacts.
- [Delete Model](https://docs.fireworks.ai/api-reference/delete-model.md)
- [Delete Reinforcement Fine-tuning Job](https://docs.fireworks.ai/api-reference/delete-reinforcement-fine-tuning-job.md)
- [Delete Reinforcement Fine-tuning Step](https://docs.fireworks.ai/api-reference/delete-reinforcement-fine-tuning-step.md)
- [Delete Response](https://docs.fireworks.ai/api-reference/delete-response.md): Deletes a model response by its ID. Once deleted, the response data will be gone immediately and permanently.
- [Delete secret](https://docs.fireworks.ai/api-reference/delete-secret.md)
- [Delete Supervised Fine-tuning Job](https://docs.fireworks.ai/api-reference/delete-supervised-fine-tuning-job.md)
- [Execute one training step for keep-alive Reinforcement Fine-tuning Step](https://docs.fireworks.ai/api-reference/execute-reinforcement-fine-tuning-step.md)
- [Generate an image with FLUX.1 [schnell] FP8](https://docs.fireworks.ai/api-reference/generate-a-new-image-from-a-text-prompt.md)
- [Generate or edit an image with FLUX.1 Kontext](https://docs.fireworks.ai/api-reference/generate-or-edit-image-using-flux-kontext.md)
- [Get Account](https://docs.fireworks.ai/api-reference/get-account.md)
- [Get Batch Inference Job](https://docs.fireworks.ai/api-reference/get-batch-inference-job.md)
- [Check Batch Status](https://docs.fireworks.ai/api-reference/get-batch-status.md)
- [Get Dataset](https://docs.fireworks.ai/api-reference/get-dataset.md)
- [Get Dataset Download Endpoint](https://docs.fireworks.ai/api-reference/get-dataset-download-endpoint.md)
- [Get Dataset Upload Endpoint](https://docs.fireworks.ai/api-reference/get-dataset-upload-endpoint.md)
- [Get LoRA](https://docs.fireworks.ai/api-reference/get-deployed-model.md)
- [Get Deployment](https://docs.fireworks.ai/api-reference/get-deployment.md)
- [Get Deployment Shape](https://docs.fireworks.ai/api-reference/get-deployment-shape.md)
- [Get Deployment Shape Version](https://docs.fireworks.ai/api-reference/get-deployment-shape-version.md)
- [Get dpo job](https://docs.fireworks.ai/api-reference/get-dpo-job.md)
- [Get dpo job metrics file endpoint](https://docs.fireworks.ai/api-reference/get-dpo-job-metrics-file-endpoint.md)
- [Get Evaluation Job](https://docs.fireworks.ai/api-reference/get-evaluation-job.md)
- [Get Evaluation Job execution logs (stream log endpoint + tracing IDs).](https://docs.fireworks.ai/api-reference/get-evaluation-job-log-endpoint.md)
- [Get Evaluator](https://docs.fireworks.ai/api-reference/get-evaluator.md): Retrieves an evaluator by name. Use this to monitor build progress after creation (**step 6** in the [Create Evaluator](/api-reference/create-evaluator) workflow).
- [Get Evaluator Build Log Endpoint](https://docs.fireworks.ai/api-reference/get-evaluator-build-log-endpoint.md): Returns a signed URL to download the evaluator's build logs. Useful for debugging `BUILD_FAILED` state.
- [Get Evaluator Source Code Endpoint](https://docs.fireworks.ai/api-reference/get-evaluator-source-code-endpoint.md): Returns a signed URL to download the evaluator's source code archive. Useful for debugging or reviewing the uploaded code.
- [Get Evaluator Upload Endpoint](https://docs.fireworks.ai/api-reference/get-evaluator-upload-endpoint.md): Returns signed URLs for uploading evaluator source code (**step 3** in the [Create Evaluator](/api-reference/create-evaluator) workflow). After receiving the signed URL, upload your `.tar.gz` archive using HTTP `PUT` with `Content-Type: application/octet-stream` header.
- [Get generated image from FLUX.1 Kontext](https://docs.fireworks.ai/api-reference/get-generated-image-from-flux-kontex.md)
- [Get Model](https://docs.fireworks.ai/api-reference/get-model.md)
- [Get Model Download Endpoint](https://docs.fireworks.ai/api-reference/get-model-download-endpoint.md)
- [Get Model Upload Endpoint](https://docs.fireworks.ai/api-reference/get-model-upload-endpoint.md)
- [Get Reinforcement Fine-tuning Job](https://docs.fireworks.ai/api-reference/get-reinforcement-fine-tuning-job.md)
- [Get Reinforcement Fine-tuning Step](https://docs.fireworks.ai/api-reference/get-reinforcement-fine-tuning-step.md)
- [Get Response](https://docs.fireworks.ai/api-reference/get-response.md)
- [Get Secret](https://docs.fireworks.ai/api-reference/get-secret.md): Retrieves a secret by name. Note that the `value` field is not returned in the response for security reasons. Only the `name` and `key_name` fields are included.
- [Get Supervised Fine-tuning Job](https://docs.fireworks.ai/api-reference/get-supervised-fine-tuning-job.md)
- [Get User](https://docs.fireworks.ai/api-reference/get-user.md)
- [Introduction](https://docs.fireworks.ai/api-reference/introduction.md)
- [List Accounts](https://docs.fireworks.ai/api-reference/list-accounts.md)
- [List API Keys](https://docs.fireworks.ai/api-reference/list-api-keys.md)
- [List Batch Inference Jobs](https://docs.fireworks.ai/api-reference/list-batch-inference-jobs.md)
- [List Datasets](https://docs.fireworks.ai/api-reference/list-datasets.md)
- [List LoRAs](https://docs.fireworks.ai/api-reference/list-deployed-models.md)
- [List Deployment Shapes Versions](https://docs.fireworks.ai/api-reference/list-deployment-shape-versions.md)
- [List Deployments](https://docs.fireworks.ai/api-reference/list-deployments.md)
- [List dpo jobs](https://docs.fireworks.ai/api-reference/list-dpo-jobs.md)
- [List Evaluation Jobs](https://docs.fireworks.ai/api-reference/list-evaluation-jobs.md)
- [List Evaluators](https://docs.fireworks.ai/api-reference/list-evaluators.md): Lists all evaluators for an account with pagination support.
- [List Models](https://docs.fireworks.ai/api-reference/list-models.md)
- [List Reinforcement Fine-tuning Jobs](https://docs.fireworks.ai/api-reference/list-reinforcement-fine-tuning-jobs.md)
- [List Reinforcement Fine-tuning Steps](https://docs.fireworks.ai/api-reference/list-reinforcement-fine-tuning-steps.md)
- [List Responses](https://docs.fireworks.ai/api-reference/list-responses.md): Get a list of all responses for the authenticated account.
- [List Secrets](https://docs.fireworks.ai/api-reference/list-secrets.md): Lists all secrets for an account. Note that the `value` field is not returned in the response for security reasons. Only the `name` and `key_name` fields are included for each secret.
- [List Supervised Fine-tuning Jobs](https://docs.fireworks.ai/api-reference/list-supervised-fine-tuning-jobs.md)
- [List Users](https://docs.fireworks.ai/api-reference/list-users.md)
- [Create Chat Completion](https://docs.fireworks.ai/api-reference/post-chatcompletions.md): Create a completion for the provided prompt and parameters.
- [Create Completion](https://docs.fireworks.ai/api-reference/post-completions.md): Create a completion for the provided prompt and parameters.
- [Create Response](https://docs.fireworks.ai/api-reference/post-responses.md): Creates a model response, optionally interacting with custom tools via the Model Context Protocol (MCP). This endpoint supports conversational continuation and streaming.
- [Prepare Model for different precisions](https://docs.fireworks.ai/api-reference/prepare-model.md)
- [Rerank documents](https://docs.fireworks.ai/api-reference/rerank-documents.md): Rerank documents for a query using relevance scoring
- [Resume Dpo Job](https://docs.fireworks.ai/api-reference/resume-dpo-job.md)
- [Resume Reinforcement Fine-tuning Job](https://docs.fireworks.ai/api-reference/resume-reinforcement-fine-tuning-job.md)
- [Resume Rlor Trainer Job](https://docs.fireworks.ai/api-reference/resume-reinforcement-fine-tuning-step.md)
- [Resume Supervised Fine-tuning Job](https://docs.fireworks.ai/api-reference/resume-supervised-fine-tuning-job.md)
- [Scale Deployment to a specific number of replicas or to zero](https://docs.fireworks.ai/api-reference/scale-deployment.md)
- [Undelete Deployment](https://docs.fireworks.ai/api-reference/undelete-deployment.md)
- [Update Dataset](https://docs.fireworks.ai/api-reference/update-dataset.md)
- [Update LoRA](https://docs.fireworks.ai/api-reference/update-deployed-model.md)
- [Update Deployment](https://docs.fireworks.ai/api-reference/update-deployment.md)
- [Update Evaluator](https://docs.fireworks.ai/api-reference/update-evaluator.md): Updates evaluator metadata (display_name, description, default_dataset). Changing `requirements` or `entry_point` triggers a rebuild. To upload new source code, set `prepare_code_upload: true` then follow the upload flow.
- [Update Model](https://docs.fireworks.ai/api-reference/update-model.md)
- [Update secret](https://docs.fireworks.ai/api-reference/update-secret.md)
- [Update User](https://docs.fireworks.ai/api-reference/update-user.md)
- [Upload Dataset Files](https://docs.fireworks.ai/api-reference/upload-dataset-files.md): 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).
- [Validate Dataset Upload](https://docs.fireworks.ai/api-reference/validate-dataset-upload.md)
- [Validate Evaluator Upload](https://docs.fireworks.ai/api-reference/validate-evaluator-upload.md): Triggers server-side validation of the uploaded source code (**step 5** in the [Create Evaluator](/api-reference/create-evaluator) workflow). The server extracts and processes the archive, then builds the evaluator environment. Poll [Get Evaluator](/api-reference/get-evaluator) to monitor progress.
- [Validate Model Upload](https://docs.fireworks.ai/api-reference/validate-model-upload.md)
- [Autoscaling](https://docs.fireworks.ai/deployments/autoscaling.md): Configure how your deployment scales based on traffic
- [Performance benchmarking](https://docs.fireworks.ai/deployments/benchmarking.md): Measure and optimize your deployment's performance with load testing
- [Client-side performance optimization](https://docs.fireworks.ai/deployments/client-side-performance-optimization.md): Optimize your client code for maximum performance with dedicated deployments
- [Direct routing (deprecated)](https://docs.fireworks.ai/deployments/direct-routing.md): Direct routing is deprecated. Migrate to the API gateway for the same low latency plus multi-region reliability.
- [Exporting Metrics](https://docs.fireworks.ai/deployments/exporting-metrics.md): Export metrics from your dedicated deployments to your observability stack
- [Regions](https://docs.fireworks.ai/deployments/regions.md): Fireworks runs a global fleet of hardware on which you can deploy your models.
- [Reserved capacity](https://docs.fireworks.ai/deployments/reservations.md)
- [Routers](https://docs.fireworks.ai/deployments/routers.md): Distribute traffic across multiple deployments for A/B testing, traffic migration, and load distribution.
- [Speculative Decoding](https://docs.fireworks.ai/deployments/speculative-decoding.md): Speed up generation with draft models and n-gram speculation
- [Cloud Integrations](https://docs.fireworks.ai/ecosystem/integrations.md): Cloud Integrations
- [Agent Frameworks](https://docs.fireworks.ai/ecosystem/integrations/agent-frameworks.md): Build production-ready AI agents with Fireworks and leading open-source frameworks
- [Claude Code](https://docs.fireworks.ai/ecosystem/integrations/claude-code.md): Use Claude Code with Fireworks AI models
- [MLOps & Observability](https://docs.fireworks.ai/ecosystem/integrations/mlops-observability.md): Track and monitor your Fireworks AI deployments with leading MLOps and observability platforms
- [Cookbooks](https://docs.fireworks.ai/examples/cookbooks.md): Interactive Jupyter notebooks demonstrating advanced use cases and best practices with Fireworks AI
- [Courses](https://docs.fireworks.ai/examples/introduction.md): Standalone end-to-end examples showing how to use Fireworks to solve real-world use cases
- [How do I close my Fireworks.ai account?](https://docs.fireworks.ai/faq-new/account-access/how-do-i-close-my-fireworksai-account.md)
- [I have multiple Fireworks accounts. When I try to login with Google on Fireworks' web UI, I'm getting signed into the wrong account. How do I fix this?](https://docs.fireworks.ai/faq-new/account-access/i-have-multiple-fireworks-accounts-when-i-try-to-login-with-google-on-fireworks.md)
- [What email does GitHub authentication use?](https://docs.fireworks.ai/faq-new/account-access/what-email-does-github-authentication-use.md)
- [What email does LinkedIn authentication use?](https://docs.fireworks.ai/faq-new/account-access/what-email-does-linkedin-authentication-use.md)
- [What should I do if I can't access my company account after being invited when I already have a personal account?](https://docs.fireworks.ai/faq-new/account-access/what-should-i-do-if-i-cant-access-my-company-account-after-being-invited-when-i.md)
- [Are there discounts for bulk usage?](https://docs.fireworks.ai/faq-new/billing-pricing/are-there-discounts-for-bulk-usage.md)
- [Are there extra fees for serving fine-tuned models?](https://docs.fireworks.ai/faq-new/billing-pricing/are-there-extra-fees-for-serving-fine-tuned-models.md)
- [How does billing and credit usage work?](https://docs.fireworks.ai/faq-new/billing-pricing/how-does-billing-and-credit-usage-work.md)
- [How many tokens per image?](https://docs.fireworks.ai/faq-new/billing-pricing/how-many-tokens-per-image.md): Learn how to calculate token usage for images in vision models and understand pricing implications
- [How much does Fireworks cost?](https://docs.fireworks.ai/faq-new/billing-pricing/how-much-does-fireworks-cost.md)
- [Is prompt caching billed differently for serverless models?](https://docs.fireworks.ai/faq-new/billing-pricing/is-prompt-caching-billed-differently.md)
- [How do credits work?](https://docs.fireworks.ai/faq-new/billing-pricing/what-happens-when-i-finish-my-1-dollar-credit.md)
- [Why might my account be suspended even with remaining credits?](https://docs.fireworks.ai/faq-new/billing-pricing/why-might-my-account-be-suspended-even-with-remaining-credits.md)
- [Are there any quotas for serverless?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/are-there-any-quotas-for-serverless.md)
- [Do you provide notice before removing model availability?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/do-you-provide-notice-before-removing-model-availability.md)
- [Do you support Auto Scaling?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/do-you-support-auto-scaling.md)
- [How does autoscaling affect my costs?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/how-does-autoscaling-affect-my-costs.md)
- [How does billing and scaling work for on-demand GPU deployments?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/how-does-billing-and-scaling-work-for-on-demand-gpu-deployments.md)
- [How does billing work for on-demand deployments?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/how-does-billing-work-for-on-demand-deployments.md)
- [How does the system scale?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/how-does-the-system-scale.md)
- [Are there SLAs for serverless?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/is-latency-guaranteed-for-serverless-models.md)
- [What are the rate limits for on-demand deployments?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/what-are-the-rate-limits-for-on-demand-deployments.md)
- [What factors affect the number of simultaneous requests that can be handled?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/what-factors-affect-the-number-of-simultaneous-requests-that-can-be-handled.md)
- [What’s the supported throughput?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/whats-the-supported-throughput.md)
- [Why am I experiencing request timeout errors and slow response times with serverless LLM models?](https://docs.fireworks.ai/faq-new/deployment-infrastructure/why-am-i-experiencing-request-timeout-errors-and-slow-response-times-with-server.md)
- [Does Fireworks support custom base models?](https://docs.fireworks.ai/faq-new/models-inference/does-fireworks-support-custom-base-models.md)
- [Does the API support batching and load balancing?](https://docs.fireworks.ai/faq-new/models-inference/does-the-api-support-batching-and-load-balancing.md)
- [FLUX image generation](https://docs.fireworks.ai/faq-new/models-inference/flux-image-generation.md)
- [How do I control output image sizes when using SDXL ControlNet?](https://docs.fireworks.ai/faq-new/models-inference/how-do-i-control-output-image-sizes-when-using-sdxl-controlnet.md)
- [How to check if a model is available on serverless?](https://docs.fireworks.ai/faq-new/models-inference/how-to-check-if-a-model-is-available-on-serverless.md)
- [There’s a model I would like to use that isn’t available on Fireworks. Can I request it?](https://docs.fireworks.ai/faq-new/models-inference/theres-a-model-i-would-like-to-use-that-isnt-available-on-fireworks-can-i-reques.md)
- [What factors affect the number of simultaneous requests that can be handled?](https://docs.fireworks.ai/faq-new/models-inference/what-factors-affect-the-number-of-simultaneous-requests-that-can-be-handled.md)
- [Training Overview](https://docs.fireworks.ai/fine-tuning/cli-reference.md): Launch RFT jobs using the eval-protocol CLI
- [Remote Environment Setup](https://docs.fireworks.ai/fine-tuning/connect-environments.md): Implement the /init endpoint to run evaluations in your infrastructure
- [Deploying Fine Tuned Models](https://docs.fireworks.ai/fine-tuning/deploying-loras.md): Deploy one or multiple LoRA models fine tuned on Fireworks
- [Direct Preference Optimization](https://docs.fireworks.ai/fine-tuning/dpo-fine-tuning.md)
- [Agent Tracing](https://docs.fireworks.ai/fine-tuning/environments.md): Understand where your agent runs and how tracing enables reinforcement fine-tuning
- [Evaluators](https://docs.fireworks.ai/fine-tuning/evaluators.md): Understand the fundamentals of evaluators and reward functions in reinforcement fine-tuning
- [Supervised Fine Tuning - Text](https://docs.fireworks.ai/fine-tuning/fine-tuning-models.md)
- [Supervised Fine Tuning - Vision](https://docs.fireworks.ai/fine-tuning/fine-tuning-vlm.md): Learn how to fine-tune vision-language models on Fireworks AI with image and text datasets
- [Fine Tuning Overview](https://docs.fireworks.ai/fine-tuning/finetuning-intro.md)
- [Basics](https://docs.fireworks.ai/fine-tuning/how-rft-works.md): Understand the reinforcement learning fundamentals behind RFT
- [Managed Fine-Tuning Overview](https://docs.fireworks.ai/fine-tuning/managed-finetuning-intro.md): Fine-tune models with Fireworks-managed infrastructure — no custom code required.
- [Monitor Training](https://docs.fireworks.ai/fine-tuning/monitor-training.md): Track RFT job progress and diagnose issues in real-time
- [Parameter Tuning](https://docs.fireworks.ai/fine-tuning/parameter-tuning.md): Learn how training parameters affect model behavior and outcomes
- [Single-Turn Training Quickstart](https://docs.fireworks.ai/fine-tuning/quickstart-math.md): Train a model to be an expert at answering GSM8K math questions
- [Remote Agent Quickstart](https://docs.fireworks.ai/fine-tuning/quickstart-svg-agent.md): Train an SVG drawing agent running in a remote environment
- [Overview](https://docs.fireworks.ai/fine-tuning/reinforcement-fine-tuning-models.md): Train models using reinforcement learning in minutes
- [Cost Estimator](https://docs.fireworks.ai/fine-tuning/rft-cost-estimator.md): Estimate and optimize the cost of your RFT training jobs
- [Secure Training (BYOB)](https://docs.fireworks.ai/fine-tuning/secure-fine-tuning.md): Fine-tune models while keeping sensitive data and components under your control
- [Training Prerequisites & Validation](https://docs.fireworks.ai/fine-tuning/training-prerequisites.md): Requirements, validation checks, and common issues when launching RFT jobs
- [Checkpoints and Resume](https://docs.fireworks.ai/fine-tuning/training-sdk/cookbook/checkpoints.md): Save training progress, resume from failures, and promote checkpoints to deployable models.
- [Cookbook: DPO](https://docs.fireworks.ai/fine-tuning/training-sdk/cookbook/dpo.md): Direct Preference Optimization with pairwise data using the cookbook recipe.
- [The Cookbook](https://docs.fireworks.ai/fine-tuning/training-sdk/cookbook/overview.md): Ready-to-run training recipes for GRPO, DPO, and SFT built on top of the Training SDK.
- [Cookbook Reference](https://docs.fireworks.ai/fine-tuning/training-sdk/cookbook/reference.md): Configuration classes, checkpoint utilities, and gradient accumulation normalization for cookbook recipes.
- [Cookbook: Reinforcement Learning](https://docs.fireworks.ai/fine-tuning/training-sdk/cookbook/rl.md): GRPO training with policy/reference trainers, reward scoring, and serving hotload via cookbook recipes.
- [Cookbook: SFT](https://docs.fireworks.ai/fine-tuning/training-sdk/cookbook/sft.md): Supervised fine-tuning via the cookbook's sft_loop recipe.
- [Introduction](https://docs.fireworks.ai/fine-tuning/training-sdk/introduction.md): Fireworks Training SDK — custom training loops with full Python control over objectives, while Fireworks handles distributed GPU infrastructure.
- [Loss Functions](https://docs.fireworks.ai/fine-tuning/training-sdk/loss-functions.md): Built-in loss functions and custom objectives via forward_backward_custom.
- [Quickstart](https://docs.fireworks.ai/fine-tuning/training-sdk/quickstart.md): Get a custom training loop running in minutes with the Fireworks Training SDK.
- [Cleanup and Teardown](https://docs.fireworks.ai/fine-tuning/training-sdk/reference/cleanup.md): Delete trainer jobs and deployments after experiments to avoid leaked resources.
- [DeploymentManager](https://docs.fireworks.ai/fine-tuning/training-sdk/reference/deployment-manager.md): Create and manage deployments used as sampling and hotload targets during training.
- [DeploymentSampler](https://docs.fireworks.ai/fine-tuning/training-sdk/reference/deployment-sampler.md): Client-side tokenized sampling from inference deployments for training and evaluation.
- [FireworksClient](https://docs.fireworks.ai/fine-tuning/training-sdk/reference/fireworks-client.md): Account-level operations that don't require a running trainer job.
- [FiretitanServiceClient & TrainingClient](https://docs.fireworks.ai/fine-tuning/training-sdk/reference/service-client.md): Connect to a trainer endpoint and use the training client for forward/backward passes, optimizer steps, and checkpointing.
- [TrainerJobManager](https://docs.fireworks.ai/fine-tuning/training-sdk/reference/trainer-job-manager.md): Create, inspect, resume, and delete service-mode RLOR trainer jobs.
- [WeightSyncer](https://docs.fireworks.ai/fine-tuning/training-sdk/reference/weight-syncer.md): Manages the checkpoint-then-sync lifecycle with automatic base/delta chain tracking.
- [Saving and Loading](https://docs.fireworks.ai/fine-tuning/training-sdk/saving-and-loading.md): Save checkpoints for serving and persist train state for resume.
- [Training and Sampling](https://docs.fireworks.ai/fine-tuning/training-sdk/training-and-sampling.md): End-to-end SDK walkthrough: bootstrap resources, train, checkpoint, and sample through a serving deployment.
- [Training Shapes](https://docs.fireworks.ai/fine-tuning/training-sdk/training-shapes.md): Pre-configured GPU and model training profiles that simplify distributed training setup.
- [Using Secrets](https://docs.fireworks.ai/fine-tuning/using-secret-in-evaluator.md): Learn how to create secrets that can be utilized within your reward function.
- [Warm Start from Fine-Tuned Models](https://docs.fireworks.ai/fine-tuning/warm-start.md): Continue training from a previously fine-tuned model with RFT
- [Training Guide: UI](https://docs.fireworks.ai/fine-tuning/web-ui-guide.md): Launch RFT jobs using the Fireworks dashboard
- [Weighted Training](https://docs.fireworks.ai/fine-tuning/weighted-training.md): Control which samples have greater influence during RFT training
- [Fire Pass Setup](https://docs.fireworks.ai/firepass.md): Kimi K2.5 Turbo for personal agentic coding — Fire Pass (Early Access), first week free, then $7/week
- [Concepts](https://docs.fireworks.ai/getting-started/concepts.md): This document outlines basic Fireworks AI concepts.
- [Build with Fireworks AI](https://docs.fireworks.ai/getting-started/introduction.md): Fast inference and fine-tuning for open source models
- [Deployments Quickstart](https://docs.fireworks.ai/getting-started/ondemand-quickstart.md): Deploy models on dedicated GPUs in minutes
- [Serverless Quickstart](https://docs.fireworks.ai/getting-started/quickstart.md): Make your first Serverless API call in minutes
- [Batch API](https://docs.fireworks.ai/guides/batch-inference.md): Process large-scale async workloads
- [Completions API](https://docs.fireworks.ai/guides/completions-api.md): Use the completions API for raw text generation with custom prompt templates
- [Tool Calling](https://docs.fireworks.ai/guides/function-calling.md): Connect models to external tools and APIs
- [Inference Error Codes](https://docs.fireworks.ai/guides/inference-error-codes.md): Common error codes, their meanings, and resolutions for inference requests
- [Deployments](https://docs.fireworks.ai/guides/ondemand-deployments.md): Configure and manage on-demand deployments on dedicated GPUs
- [Using predicted outputs](https://docs.fireworks.ai/guides/predicted-outputs.md): Use Predicted Outputs to boost output generation speeds for editing / rewriting use cases
- [Prompt caching](https://docs.fireworks.ai/guides/prompt-caching.md)
- [Speech to Text](https://docs.fireworks.ai/guides/querying-asr-models.md): Convert audio to text with streaming and pre-recorded transcription
- [Embeddings & Reranking](https://docs.fireworks.ai/guides/querying-embeddings-models.md): Generate embeddings and rerank results for semantic search
- [Text Models](https://docs.fireworks.ai/guides/querying-text-models.md): Query, track and manage inference for text models
- [Vision Models](https://docs.fireworks.ai/guides/querying-vision-language-models.md): Query vision-language models to analyze images and visual content
- [Rate Limits & Quotas](https://docs.fireworks.ai/guides/quotas_usage/rate-limits.md): Understand and manage your rate limits, spend limits and quotas
- [Reasoning](https://docs.fireworks.ai/guides/reasoning.md): How to use reasoning with Fireworks models
- [Which model should I use?](https://docs.fireworks.ai/guides/recommended-models.md): Find the best open models for your use case or migrate from closed source models like Claude, GPT, and Gemini
- [Responses API](https://docs.fireworks.ai/guides/response-api.md)
- [Audit & Access Logs](https://docs.fireworks.ai/guides/security_compliance/audit_logs.md): Monitor and track account activities with audit logging for Enterprise accounts
- [Zero Data Retention](https://docs.fireworks.ai/guides/security_compliance/data_handling.md): Data retention policies at Fireworks
- [Data Security](https://docs.fireworks.ai/guides/security_compliance/data_security.md): How we secure and handle your data for inference and training
- [Video & Audio Inputs](https://docs.fireworks.ai/guides/video-audio-inputs.md): Query multimodal models to process video and audio content directly
- [Quantization](https://docs.fireworks.ai/models/quantization.md): Reduce model precision to improve performance and lower costs
- [Custom Models](https://docs.fireworks.ai/models/uploading-custom-models.md): Upload, verify, and deploy your own models from Hugging Face or elsewhere
- [Structured Outputs](https://docs.fireworks.ai/structured-responses/structured-response-formatting.md): Enforce output formats using JSON schemas or custom grammars
- [Anthropic compatibility](https://docs.fireworks.ai/tools-sdks/anthropic-compatibility.md): Use Anthropic SDKs with Fireworks, and understand the supported surface for the Anthropic-compatible Messages API.
- [firectl account get](https://docs.fireworks.ai/tools-sdks/firectl/commands/account-get.md): Prints information about an account.
- [firectl account list](https://docs.fireworks.ai/tools-sdks/firectl/commands/account-list.md): Prints all accounts the current signed-in user has access to.
- [firectl api-key create](https://docs.fireworks.ai/tools-sdks/firectl/commands/api-key-create.md): Creates an API key for the signed in user or a specified service account user.
- [firectl api-key delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/api-key-delete.md): Deletes an API key.
- [firectl api-key list](https://docs.fireworks.ai/tools-sdks/firectl/commands/api-key-list.md): Prints all API keys for the signed in user.
- [firectl audit-logs list](https://docs.fireworks.ai/tools-sdks/firectl/commands/audit-logs-list.md): Lists audit logs for the signed in user.
- [Authentication](https://docs.fireworks.ai/tools-sdks/firectl/commands/authentication.md): Authentication for access to your account
- [firectl batch-inference-job create](https://docs.fireworks.ai/tools-sdks/firectl/commands/batch-inference-job-create.md): Creates a batch inference job.
- [firectl batch-inference-job delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/batch-inference-job-delete.md): Deletes a batch inference job.
- [firectl batch-inference-job get](https://docs.fireworks.ai/tools-sdks/firectl/commands/batch-inference-job-get.md): Retrieves information about a batch inference job.
- [firectl batch-inference-job list](https://docs.fireworks.ai/tools-sdks/firectl/commands/batch-inference-job-list.md): Lists all batch inference jobs in an account.
- [firectl billing export-metrics](https://docs.fireworks.ai/tools-sdks/firectl/commands/billing-export-metrics.md): Exports billing metrics
- [firectl billing list-invoices](https://docs.fireworks.ai/tools-sdks/firectl/commands/billing-list-invoices.md): Prints information about invoices.
- [firectl credit-redemption list](https://docs.fireworks.ai/tools-sdks/firectl/commands/credit-redemption-list.md): Lists credit code redemptions for the current account.
- [firectl credit-redemption redeem](https://docs.fireworks.ai/tools-sdks/firectl/commands/credit-redemption-redeem.md): Redeems a credit code.
- [firectl dataset create](https://docs.fireworks.ai/tools-sdks/firectl/commands/dataset-create.md): Creates and uploads a dataset.
- [firectl dataset delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/dataset-delete.md): Deletes a dataset.
- [firectl dataset download](https://docs.fireworks.ai/tools-sdks/firectl/commands/dataset-download.md): Downloads a dataset to a local directory.
- [firectl dataset get](https://docs.fireworks.ai/tools-sdks/firectl/commands/dataset-get.md): Prints information about a dataset.
- [firectl dataset list](https://docs.fireworks.ai/tools-sdks/firectl/commands/dataset-list.md): Prints all datasets in an account.
- [firectl dataset update](https://docs.fireworks.ai/tools-sdks/firectl/commands/dataset-update.md): Updates a dataset.
- [firectl deployed-model get](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployed-model-get.md): Prints information about a deployed model.
- [firectl deployed-model list](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployed-model-list.md): Prints all deployed models in the account.
- [firectl deployed-model update](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployed-model-update.md): Update a deployed model.
- [firectl deployment create](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-create.md): Creates a new deployment.
- [firectl deployment delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-delete.md): Deletes a deployment.
- [firectl deployment get](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-get.md): Prints information about a deployment.
- [firectl deployment list](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-list.md): Prints all deployments in the account.
- [firectl deployment scale](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-scale.md): Scales a deployment to a specified number of replicas.
- [firectl deployment-shape-version get](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-shape-version-get.md): Prints information about a deployment shape version.
- [firectl deployment-shape-version list](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-shape-version-list.md): Prints all deployment shape versions of this deployment shape.
- [firectl deployment undelete](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-undelete.md): Undeletes a deployment.
- [firectl deployment update](https://docs.fireworks.ai/tools-sdks/firectl/commands/deployment-update.md): Update a deployment.
- [firectl dpo-job cancel](https://docs.fireworks.ai/tools-sdks/firectl/commands/dpo-job-cancel.md): Cancels a running dpo job.
- [firectl dpo-job create](https://docs.fireworks.ai/tools-sdks/firectl/commands/dpo-job-create.md): Creates a dpo job.
- [firectl dpo-job delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/dpo-job-delete.md): Deletes a dpo job.
- [firectl dpo-job export-metrics](https://docs.fireworks.ai/tools-sdks/firectl/commands/dpo-job-export-metrics.md): Exports metrics for a dpo job.
- [firectl dpo-job get](https://docs.fireworks.ai/tools-sdks/firectl/commands/dpo-job-get.md): Retrieves information about a dpo job.
- [firectl dpo-job list](https://docs.fireworks.ai/tools-sdks/firectl/commands/dpo-job-list.md): Lists all dpo jobs in an account.
- [firectl dpo-job resume](https://docs.fireworks.ai/tools-sdks/firectl/commands/dpo-job-resume.md): Resumes a dpo job.
- [firectl evaluator-revision alias](https://docs.fireworks.ai/tools-sdks/firectl/commands/evaluator-revision-alias.md): Alias an evaluator revision
- [firectl evaluator-revision delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/evaluator-revision-delete.md): Delete an evaluator revision
- [firectl evaluator-revision get](https://docs.fireworks.ai/tools-sdks/firectl/commands/evaluator-revision-get.md): Get an evaluator revision
- [firectl evaluator-revision list](https://docs.fireworks.ai/tools-sdks/firectl/commands/evaluator-revision-list.md): List evaluator revisions
- [firectl identity-provider create](https://docs.fireworks.ai/tools-sdks/firectl/commands/identity-provider-create.md): Creates a new identity provider.
- [firectl identity-provider get](https://docs.fireworks.ai/tools-sdks/firectl/commands/identity-provider-get.md): Prints information about an identity provider.
- [firectl identity-provider list](https://docs.fireworks.ai/tools-sdks/firectl/commands/identity-provider-list.md): List identity providers for an account
- [firectl model create](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-create.md): Creates and uploads a model.
- [firectl model delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-delete.md): Deletes a model.
- [firectl model download](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-download.md): Download a model.
- [firectl model get](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-get.md): Prints information about a model.
- [firectl model list](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-list.md): Prints all models in an account.
- [firectl model load-lora](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-load-lora.md): Loads a LoRA model.
- [firectl model prepare](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-prepare.md): Prepare models for different precisions
- [firectl model unload-lora](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-unload-lora.md): Unloads a LoRA model.
- [firectl model update](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-update.md): Updates a model.
- [firectl model upload](https://docs.fireworks.ai/tools-sdks/firectl/commands/model-upload.md): Resumes or completes a model upload.
- [firectl quota get](https://docs.fireworks.ai/tools-sdks/firectl/commands/quota-get.md): Prints information about a quota.
- [firectl quota list](https://docs.fireworks.ai/tools-sdks/firectl/commands/quota-list.md): Prints all quotas.
- [firectl quota update](https://docs.fireworks.ai/tools-sdks/firectl/commands/quota-update.md): Updates a quota.
- [firectl reinforcement-fine-tuning-job cancel](https://docs.fireworks.ai/tools-sdks/firectl/commands/reinforcement-fine-tuning-job-cancel.md): Cancels a running reinforcement fine-tuning job.
- [firectl reinforcement-fine-tuning-job create](https://docs.fireworks.ai/tools-sdks/firectl/commands/reinforcement-fine-tuning-job-create.md): Creates a reinforcement fine-tuning job.
- [firectl reinforcement-fine-tuning-job delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/reinforcement-fine-tuning-job-delete.md): Deletes a reinforcement fine-tuning job.
- [firectl reinforcement-fine-tuning-job get](https://docs.fireworks.ai/tools-sdks/firectl/commands/reinforcement-fine-tuning-job-get.md): Retrieves information about a reinforcement fine-tuning job.
- [firectl reinforcement-fine-tuning-job list](https://docs.fireworks.ai/tools-sdks/firectl/commands/reinforcement-fine-tuning-job-list.md): Lists all reinforcement fine-tuning jobs in an account.
- [firectl reinforcement-fine-tuning-job resume](https://docs.fireworks.ai/tools-sdks/firectl/commands/reinforcement-fine-tuning-job-resume.md): Resumes a failed reinforcement fine-tuning job.
- [firectl reservation get](https://docs.fireworks.ai/tools-sdks/firectl/commands/reservation-get.md): Prints information about a reservation.
- [firectl reservation list](https://docs.fireworks.ai/tools-sdks/firectl/commands/reservation-list.md): Prints active reservations.
- [firectl secret create](https://docs.fireworks.ai/tools-sdks/firectl/commands/secret-create.md): Creates a secret for the signed in user.
- [firectl secret delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/secret-delete.md): Deletes a secret.
- [firectl secret get](https://docs.fireworks.ai/tools-sdks/firectl/commands/secret-get.md): Retrieves a secret by name.
- [firectl secret list](https://docs.fireworks.ai/tools-sdks/firectl/commands/secret-list.md): Lists all secrets for the signed in user.
- [firectl secret update](https://docs.fireworks.ai/tools-sdks/firectl/commands/secret-update.md): Updates an existing secret.
- [firectl set-api-key](https://docs.fireworks.ai/tools-sdks/firectl/commands/set-api-key.md): Sets the default API key in ~/.fireworks/auth.ini.
- [firectl supervised-fine-tuning-job cancel](https://docs.fireworks.ai/tools-sdks/firectl/commands/supervised-fine-tuning-job-cancel.md): Cancels a running supervised fine-tuning job.
- [firectl supervised-fine-tuning-job create](https://docs.fireworks.ai/tools-sdks/firectl/commands/supervised-fine-tuning-job-create.md): Creates a supervised fine-tuning job.
- [firectl supervised-fine-tuning-job delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/supervised-fine-tuning-job-delete.md): Deletes a supervised fine-tuning job.
- [firectl supervised-fine-tuning-job get](https://docs.fireworks.ai/tools-sdks/firectl/commands/supervised-fine-tuning-job-get.md): Retrieves information about a supervised fine-tuning job.
- [firectl supervised-fine-tuning-job list](https://docs.fireworks.ai/tools-sdks/firectl/commands/supervised-fine-tuning-job-list.md): Lists all supervised fine-tuning jobs in an account.
- [firectl upgrade](https://docs.fireworks.ai/tools-sdks/firectl/commands/upgrade.md): Upgrades the firectl binary to the latest version.
- [firectl user create](https://docs.fireworks.ai/tools-sdks/firectl/commands/user-create.md): Creates a new user.
- [firectl user delete](https://docs.fireworks.ai/tools-sdks/firectl/commands/user-delete.md): Deletes a user.
- [firectl user get](https://docs.fireworks.ai/tools-sdks/firectl/commands/user-get.md): Prints information about a user.
- [firectl user list](https://docs.fireworks.ai/tools-sdks/firectl/commands/user-list.md): Prints all users in the account.
- [firectl user update](https://docs.fireworks.ai/tools-sdks/firectl/commands/user-update.md): Updates a user.
- [firectl version](https://docs.fireworks.ai/tools-sdks/firectl/commands/version.md): Prints the version of firectl
- [firectl whoami](https://docs.fireworks.ai/tools-sdks/firectl/commands/whoami.md): Shows the currently authenticated user
- [Getting started](https://docs.fireworks.ai/tools-sdks/firectl/firectl.md): Learn to create, deploy, and manage resources using Firectl
- [OpenAI compatibility](https://docs.fireworks.ai/tools-sdks/openai-compatibility.md)
- [Python SDK](https://docs.fireworks.ai/tools-sdks/python-sdk.md)
- [Changelog](https://docs.fireworks.ai/updates/changelog.md)

## OpenAPI Specs

- [text-completion.openapi](https://docs.fireworks.ai/text-completion.openapi.yaml)
- [responses.openapi](https://docs.fireworks.ai/responses.openapi.yaml)
- [openapi](https://docs.fireworks.ai/openapi.yml)
- [merged.openapi](https://docs.fireworks.ai/merged.openapi.yaml)
- [gateway.openapi](https://docs.fireworks.ai/gateway.openapi.yaml)
- [gateway-extra.openapi](https://docs.fireworks.ai/gateway-extra.openapi.yaml)
- [anthropic-messages.openapi](https://docs.fireworks.ai/anthropic-messages.openapi.json)

## Optional

- [Demos](https://demos.fireworks.ai)


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