# Together AI docs

> Documentation for the Together AI platform for inference and training.

## Docs

- [Manage your account](https://docs.together.ai/docs/account-management.md): Sign up for Together AI, get your API key, and manage your account settings
- [Agent integrations](https://docs.together.ai/docs/agent-integrations.md): Use OSS agent frameworks with Together AI.
- [Coding agent setup](https://docs.together.ai/docs/agent-skills.md): Make your AI coding agent Together-AI-aware with ready-made skills for code generation and an MCP server for live docs lookup.
- [Agno](https://docs.together.ai/docs/agno.md): Using Agno with Together AI
- [Overview](https://docs.together.ai/docs/ai-evaluations.md): Learn how to run LLM-as-a-Judge evaluations
- [AI evaluations UI](https://docs.together.ai/docs/ai-evaluations-ui.md): Guide to using the AI Evaluations UI for model assessment
- [Build an AI search engine](https://docs.together.ai/docs/ai-search-engine.md): Build an open source AI search engine inspired by Perplexity with Next.js and Together AI.
- [Build an interactive AI tutor with Llama 3.1](https://docs.together.ai/docs/ai-tutor.md): Learn how to create LlamaTutor from scratch, an open source AI tutor with 90k users.
- [Authentication](https://docs.together.ai/docs/api-keys-authentication.md): Create, manage, and authenticate with project-scoped API keys.
- [AutoGen(AG2)](https://docs.together.ai/docs/autogen.md): Using AutoGen(AG2) with Together AI
- [Credits](https://docs.together.ai/docs/billing-credits.md): Understanding credits and billing basics on Together AI.
- [Payment methods & invoices](https://docs.together.ai/docs/billing-payment-methods.md): Managing payment cards, ACH transfers, viewing invoices, and updating billing details.
- [Billing troubleshooting](https://docs.together.ai/docs/billing-troubleshooting.md): Resolving payment issues, understanding charges, and managing billing problems.
- [Usage limits & analytics](https://docs.together.ai/docs/billing-usage-limits.md): Understanding rate limits, model access, and cost analytics on Together AI.
- [Build a RAG workflow](https://docs.together.ai/docs/building-a-rag-workflow.md): Learn how to build a RAG workflow with Together AI embedding and chat endpoints!
- [Changelog](https://docs.together.ai/docs/changelog.md)
- [Set up OIDC authentication](https://docs.together.ai/docs/cluster-oidc.md): Authenticate team members to a GPU cluster's Kubernetes API using your organization's identity provider.
- [Cluster storage](https://docs.together.ai/docs/cluster-storage.md): Understand storage types, persistence, and best practices for GPU clusters
- [Composio](https://docs.together.ai/docs/composio.md): Using Composio With Together AI
- [Conditional workflow](https://docs.together.ai/docs/conditional-workflows.md): Adapt to different tasks by conditionally navigating to various LLMs and tools.
- [Quickstart](https://docs.together.ai/docs/containers-quickstart.md): Deploy your first container in 20 minutes.
- [CrewAI](https://docs.together.ai/docs/crewai.md): Using CrewAI with Together
- [Build an AI data analyst](https://docs.together.ai/docs/data-analyst-agent.md): Build an AI data analyst with code interpreter, E2B, and Together AI.
- [Overview](https://docs.together.ai/docs/dedicated-container-inference.md): Deploy custom containers on Together's managed GPU infrastructure with automatic scaling, job queues, and built-in observability.
- [Run an A/B test](https://docs.together.ai/docs/dedicated-endpoints/ab-tests.md): Compare a candidate deployment against a baseline on live traffic.
- [Concepts](https://docs.together.ai/docs/dedicated-endpoints/concepts.md): Understand the resource model and development workflow for dedicated model inference.
- [Choose a deployment profile](https://docs.together.ai/docs/dedicated-endpoints/configs.md): Pick the hardware deployment profile that your model runs on.
- [Upload a fine-tuned model](https://docs.together.ai/docs/dedicated-endpoints/custom-models.md): Serve a fine-tuned model uploaded from your machine, Hugging Face, or S3.
- [Manage endpoints and deployments](https://docs.together.ai/docs/dedicated-endpoints/manage.md): Create, update, and delete resources for dedicated model inference.
- [Migrate from v1](https://docs.together.ai/docs/dedicated-endpoints/migrate-from-v1.md): Move a dedicated endpoint from the v1 API to the v2 dedicated model inference resource model.
- [Supported models](https://docs.together.ai/docs/dedicated-endpoints/models.md): View the supported models you can deploy or fine-tune for dedicated model inference.
- [Monitor endpoints and deployments](https://docs.together.ai/docs/dedicated-endpoints/monitoring.md): Monitor endpoint and deployment metrics with built-in dashboards and a Prometheus-compatible metrics endpoint.
- [Overview](https://docs.together.ai/docs/dedicated-endpoints/overview.md): Deploy a model for inference on dedicated GPUs.
- [Pricing](https://docs.together.ai/docs/dedicated-endpoints/pricing.md): Billing and pricing details for dedicated model inference.
- [Quickstart](https://docs.together.ai/docs/dedicated-endpoints/quickstart.md): Deploy a model on dedicated hardware in just a few minutes.
- [Send requests](https://docs.together.ai/docs/dedicated-endpoints/requests.md): After deploying a model, send requests using the shared inference API.
- [Overview](https://docs.together.ai/docs/dedicated-endpoints/route-traffic.md): Learn how to route traffic to a deployment, and explore advanced strategies to change how traffic moves over time.
- [Configure autoscaling](https://docs.together.ai/docs/dedicated-endpoints/scaling.md): Autoscale a deployment between replica bounds, pick the right scaling metric, and understand the cost tradeoff.
- [Run a shadow experiment](https://docs.together.ai/docs/dedicated-endpoints/shadow-experiments.md): Mirror a sampled fraction of endpoint traffic to a target deployment without affecting the client response.
- [Split traffic across deployments](https://docs.together.ai/docs/dedicated-endpoints/split-traffic.md): Run multiple deployments on one endpoint and split requests between them by weight.
- [Image generation with Flux2](https://docs.together.ai/docs/dedicated_containers_image.md): Deploy a Flux2 image generation model on Together's managed GPU infrastructure using dedicated containers.
- [Video generation with Wan 2.1](https://docs.together.ai/docs/dedicated_containers_video.md): Deploy a multi-GPU video generation model on Together's managed GPU infrastructure using dedicated containers.
- [DeepSeek V4 Pro quickstart](https://docs.together.ai/docs/deepseek-v4-quickstart.md): Call DeepSeek V4 Pro on Together for hybrid reasoning, long-context, and tool-using workloads.
- [Jig CLI](https://docs.together.ai/docs/deployments-jig.md): Build, push, and deploy containers to Together's managed GPU infrastructure.
- [Queue API](https://docs.together.ai/docs/deployments-queue.md): Submit, monitor, and manage asynchronous jobs for your Dedicated Container deployments.
- [Sprocket SDK](https://docs.together.ai/docs/deployments-sprocket.md): A Python SDK for building inference workers that support both synchronous and asynchronous requests via Together's platform.
- [Deprecations](https://docs.together.ai/docs/deprecations.md): Together AI's model lifecycle policy, including upgrades, redirects, and deprecation schedules.
- [DSPy](https://docs.together.ai/docs/dspy.md): Using DSPy with Together AI
- [Error codes](https://docs.together.ai/docs/error-codes.md): An overview on error status codes, causes, and quick fix solutions.
- [Supported models](https://docs.together.ai/docs/evaluations-supported-models.md): Supported models for Evaluations
- [Bring your own model](https://docs.together.ai/docs/fine-tuning/byom.md): Fine-tune a Hugging Face model that isn't in the Together catalog.
- [Data preparation](https://docs.together.ai/docs/fine-tuning/data-preparation.md): Format your training file as JSONL or Parquet to match your task, then validate and upload.
- [Deploy a fine-tuned model](https://docs.together.ai/docs/fine-tuning/deployment.md): Serve your fine-tuned model on a dedicated endpoint or download it for local inference.
- [Early stopping](https://docs.together.ai/docs/fine-tuning/early-stopping.md): Halt a fine-tuning job when validation loss stops improving.
- [Function-calling fine-tuning](https://docs.together.ai/docs/fine-tuning/function-calling.md): Train a model to invoke tools and structured functions reliably.
- [LoRA vs. full fine-tuning](https://docs.together.ai/docs/fine-tuning/lora-vs-full.md): Choose between LoRA and full fine-tuning, then tune LoRA's rank and target modules.
- [Monitor a fine-tuning job](https://docs.together.ai/docs/fine-tuning/monitoring.md): Poll job status, retrieve per-step loss and evaluation metrics, and stream training progress to Weights & Biases.
- [Overview](https://docs.together.ai/docs/fine-tuning/overview.md): Adapt a base model to a task by training it on your data.
- [Preference fine-tuning](https://docs.together.ai/docs/fine-tuning/preference-tuning.md): Align a model with paired preferred and dispreferred responses using DPO.
- [Pricing](https://docs.together.ai/docs/fine-tuning/pricing.md): Fine-tuning is billed per token processed, scaled by model size, training method, and training type.
- [Fine-tuning quickstart](https://docs.together.ai/docs/fine-tuning/quickstart.md): Prepare a conversational dataset, launch a LoRA job on Qwen3.5 9B, and evaluate the fine-tuned model.
- [Reasoning fine-tuning](https://docs.together.ai/docs/fine-tuning/reasoning.md): Train a reasoning model on chain-of-thought data.
- [Supervised fine-tuning](https://docs.together.ai/docs/fine-tuning/supervised.md): Train a model on demonstration data with supervised fine-tuning (SFT).
- [Supported models](https://docs.together.ai/docs/fine-tuning/supported-models.md): Every base model available for fine-tuning, with context length and batch size limits.
- [Troubleshooting fine-tuning jobs](https://docs.together.ai/docs/fine-tuning/troubleshooting.md): Diagnose failed or cancelled fine-tuning jobs, understand job timing, and resolve common errors.
- [Vision fine-tuning](https://docs.together.ai/docs/fine-tuning/vision.md): Fine-tune vision-language models on image and text data with Together AI.
- [GLM-5.2 quickstart](https://docs.together.ai/docs/glm-5.2-quickstart.md): Get the most out of GLM-5.2 for long-horizon coding and agentic tasks.
- [GPT-OSS quickstart](https://docs.together.ai/docs/gpt-oss.md): Get started with OpenAI's GPT-OSS, open-source reasoning model duo.
- [API & integrations](https://docs.together.ai/docs/gpu-clusters-api.md): Manage clusters programmatically with the Together CLI, REST API, and SkyPilot
- [Billing & pricing](https://docs.together.ai/docs/gpu-clusters-billing.md): Understand billing, pricing, and lifecycle policies for GPU Clusters
- [Cluster management](https://docs.together.ai/docs/gpu-clusters-management.md): Manage, scale, and operate your GPU clusters
- [Overview](https://docs.together.ai/docs/gpu-clusters-overview.md): High-performance GPU clusters for training, fine-tuning, and large-scale AI workloads
- [Quickstart](https://docs.together.ai/docs/gpu-clusters-quickstart.md): Get started with GPU Clusters in minutes.
- [Overview](https://docs.together.ai/docs/guides.md): Quickstarts and step-by-step guides for building with Together AI.
- [Health checks](https://docs.together.ai/docs/health-checks.md): Monitor GPU node health with active diagnostic tests and continuous passive monitoring.
- [Build a lovable clone with Kimi K2](https://docs.together.ai/docs/how-to-build-a-lovable-clone-with-kimi-k2.md): Learn how to build a full-stack Next.js app that can generate React apps with a single prompt.
- [Build a coding agent](https://docs.together.ai/docs/how-to-build-coding-agents.md): Build a simple code editing agent from scratch in 400 lines of code.
- [Build a phone voice agent with Together AI](https://docs.together.ai/docs/how-to-build-phone-voice-agent.md): Create a real-time phone voice agent from scratch with Twilio Media Streams, Together AI realtime STT, chat completions, realtime TTS, and local voice activity detection.
- [Build an audio transcription app with Whisper](https://docs.together.ai/docs/how-to-build-real-time-audio-transcription-app.md): Learn how to build a real-time AI audio transcription app with Whisper, Next.js, and Together AI.
- [Implement contextual RAG from Anthropic](https://docs.together.ai/docs/how-to-implement-contextual-rag-from-anthropic.md): An open source line-by-line implementation of contextual RAG from Anthropic.
- [Improve search with rerankers](https://docs.together.ai/docs/how-to-improve-search-with-rerankers.md): Improve semantic search quality with reranker models.
- [Configure Cline with Together AI models](https://docs.together.ai/docs/how-to-use-cline.md): Learn how to power Cline (an AI coding agent) with Together AI models.
- [Configure OpenClaw with Together AI models](https://docs.together.ai/docs/how-to-use-openclaw.md): Learn how to power OpenClaw (an autonomous agent) with Together AI models.
- [Configure OpenCode with Together AI models](https://docs.together.ai/docs/how-to-use-opencode.md): Learn how to power OpenCode (a powerful terminal-based AI coding agent) with Together AI models.
- [Configure Qwen Code with Together AI models](https://docs.together.ai/docs/how-to-use-qwen-code.md): Learn how to power Qwen Code with Together AI models.
- [Configure Claude Code, Codex, and ChatGPT with Together AI models](https://docs.together.ai/docs/how-to-use-togetherlink.md): Use TogetherLink to run Claude Code, Codex CLI, ChatGPT Desktop, Pi Code, and OpenCode with models hosted by Together AI.
- [IAM model](https://docs.together.ai/docs/identity-access-management.md): How users, credentials, and resources are organized across the Together platform
- [Manage batch jobs](https://docs.together.ai/docs/inference/batch/manage.md): Status, results, errors, and operational reference for the Together Batch API.
- [Overview](https://docs.together.ai/docs/inference/batch/overview.md): Run asynchronous batch workloads at up to 50% lower cost.
- [Run a batch job](https://docs.together.ai/docs/inference/batch/tutorial.md): Prepare a JSONL file, upload it, start a batch job, poll until it finishes, and retrieve results.
- [Log probabilities](https://docs.together.ai/docs/inference/chat/logprobs.md): Return per-token log probabilities to measure model confidence and route low-confidence outputs to a stronger model.
- [Send chat completions](https://docs.together.ai/docs/inference/chat/overview.md): Query chat models with single prompts, multi-turn conversations, and system prompts.
- [Parameters](https://docs.together.ai/docs/inference/chat/parameters.md): The full list of parameters you can pass to the chat completions endpoint.
- [Reasoning](https://docs.together.ai/docs/inference/chat/reasoning.md): Use reasoning models that think step-by-step before answering.
- [Structured outputs](https://docs.together.ai/docs/inference/chat/structured-outputs.md): Use JSON mode to get structured outputs from supported chat models.
- [Generate embeddings](https://docs.together.ai/docs/inference/embeddings/embeddings.md): Turn text into vector embeddings for search, classification, recommendations, and RAG.
- [Retrieval-augmented generation](https://docs.together.ai/docs/inference/embeddings/rag.md): Build a retrieval-augmented generation pipeline with Together embeddings, rerank, and chat completions.
- [Rerank](https://docs.together.ai/docs/inference/embeddings/rerank.md): Reorder retrieved documents by relevance to a query for sharper search and RAG results.
- [Agentic function calling patterns](https://docs.together.ai/docs/inference/function-calling/agentic.md): Tool use across multiple steps or conversation turns, covering multi-step and multi-turn agent loops.
- [Function calling best practices](https://docs.together.ai/docs/inference/function-calling/best-practices.md): Design tools, write descriptions, and control tool selection so Together models call functions reliably.
- [Function calling patterns](https://docs.together.ai/docs/inference/function-calling/overview.md): Function calling lets LLMs respond with structured function names and arguments your application can execute.
- [Call functions in parallel](https://docs.together.ai/docs/inference/function-calling/parallel.md): Multiple tool calls in one response, covering parallel calls to the same tool and to different tools.
- [Call functions](https://docs.together.ai/docs/inference/function-calling/single-call.md): One tool call per response, covering simple and multiple-tool patterns.
- [Text-to-image generation](https://docs.together.ai/docs/inference/images/overview.md): Generate images from text prompts.
- [Image generation parameters](https://docs.together.ai/docs/inference/images/parameters.md): Parameter reference for the images API: dimensions, quality control, base64 responses, safety checker, and troubleshooting.
- [Image-to-image generation](https://docs.together.ai/docs/inference/images/reference-images.md): Edit or transform an existing image by passing image_url (Kontext) or reference_images (FLUX.2 and Google models).
- [OpenAI compatibility](https://docs.together.ai/docs/inference/openai-compatibility.md): Point your OpenAI Python or TypeScript client at Together AI to call open-source models without rewriting your app.
- [Overview](https://docs.together.ai/docs/inference/overview.md): Run inference on 100+ open-source models.
- [Provisioned throughput](https://docs.together.ai/docs/inference/provisioned-throughput.md): Reserved inference capacity for production workloads.
- [Recommended models](https://docs.together.ai/docs/inference/recommended-models.md): Our picks for common inference use cases.
- [Third-party integrations](https://docs.together.ai/docs/inference/sdk-integrations.md): Use Together AI models through partner SDKs and integrations.
- [Generate speech](https://docs.together.ai/docs/inference/text-to-speech/overview.md): Generate speech audio from text with Together AI text-to-speech models.
- [Text-to-speech streaming](https://docs.together.ai/docs/inference/text-to-speech/streaming.md): Stream audio over HTTP for low time-to-first-byte and access raw PCM bytes.
- [WebSocket API](https://docs.together.ai/docs/inference/text-to-speech/websocket.md): Stream text in and audio out over a single WebSocket connection for the lowest interactive latency.
- [Advanced transcription options](https://docs.together.ai/docs/inference/transcription/features.md): Speaker diarization, word-level timestamps, response formats, async support, and best practices.
- [Transcribe audio](https://docs.together.ai/docs/inference/transcription/overview.md): Transcribe and translate audio into text.
- [Streaming transcription](https://docs.together.ai/docs/inference/transcription/streaming.md): Use the real-time WebSocket API for low-latency, incremental speech-to-text.
- [Audio translation](https://docs.together.ai/docs/inference/transcription/translation.md): Translate speech in any language into English text.
- [Voice activity detection](https://docs.together.ai/docs/inference/transcription/voice-activity-detection.md): Configure voice activity detection to control how speech segments are detected in real-time transcription.
- [Audio input for videos](https://docs.together.ai/docs/inference/videos/audio-input.md): Drive video generation with an audio file for lip sync, beat-matched motion, or narration.
- [Generate videos](https://docs.together.ai/docs/inference/videos/overview.md): Generate videos from text and image prompts.
- [Video generation parameters](https://docs.together.ai/docs/inference/videos/parameters.md): Reference for video generation parameters, including guidance scale and quality control.
- [Reference images and keyframes](https://docs.together.ai/docs/inference/videos/reference-and-keyframes.md): Guide visual style with reference images and control specific frames in your video.
- [Vision-language function calling](https://docs.together.ai/docs/inference/vision/function-calling.md): Combine image understanding with tool use on Together AI vision-language models.
- [Vision input modes](https://docs.together.ai/docs/inference/vision/inputs.md): Send local images, video URLs, or multiple images to a vision model in a single request.
- [Use image inputs](https://docs.together.ai/docs/inference/vision/overview.md): Run vision-language models on Together: pass images alongside text and get structured replies, transcripts, comparisons, or extracted data.
- [Structured extraction with vision](https://docs.together.ai/docs/inference/vision/structured-extraction.md): Combine image input with a JSON schema to extract typed data from screenshots, documents, and photos.
- [Iterative workflow](https://docs.together.ai/docs/iterative-workflow.md): Iteratively call LLMs to optimize task performance.
- [Kimi K2 quickstart](https://docs.together.ai/docs/kimi-k2-quickstart.md): How to get the most out of models like Kimi K2.
- [Kimi K2 Thinking quickstart](https://docs.together.ai/docs/kimi-k2-thinking-quickstart.md): How to get the most out of reasoning models like Kimi K2 Thinking.
- [Kimi K2.6 quickstart](https://docs.together.ai/docs/kimi-k2.6-quickstart.md): Get the most out of Moonshot AI's Kimi K2.6 multimodal model for vision, reasoning, and agentic tool use.
- [Queue GPU jobs with Kueue](https://docs.together.ai/docs/kueue-on-gpu-clusters.md): Install Kueue and gate GPU jobs on quota so a shared cluster admits work as capacity frees up.
- [LangGraph](https://docs.together.ai/docs/langgraph.md): Using LangGraph with Together AI
- [Together mixture of agents (MoA)](https://docs.together.ai/docs/mixture-of-agents.md)
- [Run nanochat on instant clusters](https://docs.together.ai/docs/nanochat-on-instant-clusters.md): Train Andrej Karpathy's end-to-end ChatGPT clone on Together's on-demand GPU clusters.
- [Quickstart: Next.js](https://docs.together.ai/docs/nextjs-chat-quickstart.md): Build an app that can ask a single question or chat with an LLM using Next.js and Together AI.
- [Node repair](https://docs.together.ai/docs/node-repair.md): Restore unhealthy GPU nodes through automated recommendations or manual repair actions.
- [Build an open source NotebookLM](https://docs.together.ai/docs/open-notebooklm-pdf-to-podcast.md): Build an open source NotebookLM that turns a PDF into a podcast.
- [Organizations](https://docs.together.ai/docs/organizations.md): Create and manage your Together Organization, invite Members, and configure billing
- [Parallel workflow](https://docs.together.ai/docs/parallel-workflows.md): Execute multiple LLM calls in parallel and aggregate afterwards.
- [Privacy and security](https://docs.together.ai/docs/privacy-and-security.md): How Together handles your inputs, outputs, and account data, plus enterprise options for data residency and private networking.
- [Projects](https://docs.together.ai/docs/projects.md): Create isolated workspaces to organize resources, manage team access, and scope API keys.
- [PydanticAI](https://docs.together.ai/docs/pydanticai.md): Using PydanticAI with Together
- [Python v2 SDK Migration Guide](https://docs.together.ai/docs/pythonv2-migration-guide.md): Migrate from Together Python v1 to v2 - the new Together AI Python SDK with improved type safety and modern architecture.
- [Quickstart](https://docs.together.ai/docs/quickstart.md): Make your first request to Together AI in a few minutes.
- [FLUX.2 quickstart](https://docs.together.ai/docs/quickstart-flux.md): Learn how to use FLUX.2, the next generation image model with advanced prompting capabilities
- [FLUX Kontext quickstart](https://docs.together.ai/docs/quickstart-flux-kontext.md): Learn how to use Flux's new in-context image generation models
- [Quickstart: How to do OCR](https://docs.together.ai/docs/quickstart-how-to-do-ocr.md): A step by step guide on how to do OCR with Together AI's vision models with structured outputs
- [Retrieval-augmented generation (RAG) quickstart](https://docs.together.ai/docs/quickstart-retrieval-augmented-generation-rag.md): Build a RAG workflow in under five minutes.
- [Hugging Face Inference quickstart](https://docs.together.ai/docs/quickstart-using-hugging-face-inference.md): Use Together models with Hugging Face Inference.
- [Roles & permissions (RBAC)](https://docs.together.ai/docs/roles-permissions.md): Understand Organization and Project role-based access control (RBAC), including Admin, Developer, and Editor roles, and what each can do across Together
- [Seedance 2.0 quickstart](https://docs.together.ai/docs/seedance2.0-quickstart.md): Generate multi-shot videos with synchronized audio from text, image, video, and audio inputs.
- [Sequential workflow](https://docs.together.ai/docs/sequential-agent-workflow.md): Coordinating a chain of LLM calls to solve a complex task.
- [Available models](https://docs.together.ai/docs/serverless/models.md): Browse the catalog of available models for instant inference.
- [Overview](https://docs.together.ai/docs/serverless/overview.md): Run any supported model through a shared, per-token API with no provisioning and no minimums.
- [Rate limits](https://docs.together.ai/docs/serverless/rate-limits.md): Together AI applies dynamic per-model rate limits that scale with your sustained traffic on serverless inference.
- [Slurm management system](https://docs.together.ai/docs/slurm.md)
- [Slurm configuration](https://docs.together.ai/docs/slurm-configuration.md): Customize Slurm cluster settings to match your workload requirements
- [Slurm startup scripts](https://docs.together.ai/docs/slurm-startup-scripts.md): Configure lifecycle hook scripts that run automatically at node startup, job start, and job completion.
- [Single sign-on (SSO)](https://docs.together.ai/docs/sso.md): Connect your Identity Provider for secure, automated team access to Together
- [Support](https://docs.together.ai/docs/support.md): Search the support portal, file a ticket, or reach the Together AI team by email, Slack, or Discord.
- [Code interpreter](https://docs.together.ai/docs/together-code-interpreter.md): Execute LLM-generated code seamlessly with a simple API call.
- [Code sandbox](https://docs.together.ai/docs/together-code-sandbox.md): Level-up generative code tooling with fast, secure code sandboxes at scale
- [Architecture](https://docs.together.ai/docs/together-deployments.md): Architecture, deployment lifecycle, and core concepts for dedicated container inference.
- [Mastra quickstart](https://docs.together.ai/docs/using-together-with-mastra.md): Use Together models with Mastra.
- [Vercel AI SDK quickstart](https://docs.together.ai/docs/using-together-with-vercels-ai-sdk.md): Use Together models with the Vercel AI SDK.
- [Gang-schedule GPU jobs with Volcano](https://docs.together.ai/docs/volcano-on-gpu-clusters.md): Install the Volcano scheduler and run gang-scheduled GPU jobs on a Together Kubernetes cluster.
- [Wan 2.7 quickstart](https://docs.together.ai/docs/wan2.7-quickstart.md): Generate videos from text, images, and reference materials with the Wan 2.7 model family.
- [Agent workflows](https://docs.together.ai/docs/workflows.md): Orchestrating together multiple language model calls to solve complex tasks.
- [Together Cookbooks & Example Apps](https://docs.together.ai/examples.md): Explore our vast library of open-source cookbooks & example apps
- [Build a real-time image generator with Flux and Together AI](https://docs.together.ai/external-link-02.md)
- [Overview](https://docs.together.ai/intro.md): Run, train, and serve open-source AI models on Together AI.
- [Python Library](https://docs.together.ai/python-library.md)
- [Create audio generation request](https://docs.together.ai/reference/audio-speech.md): Generate audio from input text
- [Create realtime text-to-speech](https://docs.together.ai/reference/audio-speech-websocket.md): Establishes a WebSocket connection for real-time text-to-speech generation. This endpoint uses WebSocket protocol (wss://api.together.ai/v1/audio/speech/websocket) for bidirectional streaming communication.
- [Create audio transcription request](https://docs.together.ai/reference/audio-transcriptions.md): Transcribes audio into text
- [Real-time audio transcription via WebSocket](https://docs.together.ai/reference/audio-transcriptions-realtime.md): Establishes a WebSocket connection for real-time audio transcription. This endpoint uses WebSocket protocol (wss://api.together.ai/v1/realtime) for bidirectional streaming communication.
- [Create audio translation request](https://docs.together.ai/reference/audio-translations.md): Translates audio into English
- [Cancel a batch job](https://docs.together.ai/reference/batch-cancel.md): Cancel a batch job by ID
- [Create a batch job](https://docs.together.ai/reference/batch-create.md): Create a new batch job with the given input file and endpoint
- [Get a batch job](https://docs.together.ai/reference/batch-get.md): Get details of a batch job by ID
- [List batch jobs](https://docs.together.ai/reference/batch-list.md): List all batch jobs for the authenticated user
- [Create chat completion](https://docs.together.ai/reference/chat-completions.md): Generate a model response for a given chat conversation. Supports single queries and multi-turn conversations with system, user, and assistant messages.
- [Clusters](https://docs.together.ai/reference/cli/clusters.md): Reserve, configure, and manage GPU clusters from your terminal.
- [Endpoints](https://docs.together.ai/reference/cli/endpoints.md): Create, update, and manage dedicated inference endpoints from your terminal.
- [Endpoints](https://docs.together.ai/reference/cli/endpoints-beta.md): Deploy and manage dedicated inference endpoints from your terminal.
- [Evals](https://docs.together.ai/reference/cli/evals.md): Create and manage model-evaluation jobs from your terminal, including classify, score, and compare evals.
- [Files](https://docs.together.ai/reference/cli/files.md): Upload and manage datasets for use in fine-tuning, evals, and batch inference.
- [Fine-tuning](https://docs.together.ai/reference/cli/finetune.md): Create, monitor, and manage fine-tuning jobs from your terminal.
- [Get started](https://docs.together.ai/reference/cli/getting-started.md): Install the Together CLI to deploy endpoints, fine-tune models, and manage GPU clusters from your terminal.
- [Jig CLI reference](https://docs.together.ai/reference/cli/jig.md): CLI commands, pyproject.toml configuration, environment variables, and Python SDK for dedicated containers.
- [Models](https://docs.together.ai/reference/cli/models.md): List Together AI models and upload your own from Hugging Face or S3.
- [Models](https://docs.together.ai/reference/cli/models-beta.md): Register, upload, and inspect models and adapters for dedicated model inference from your terminal.
- [Telemetry](https://docs.together.ai/reference/cli/telemetry.md): Understand what the Together CLI tracks, how to opt out, and where the local config file lives.
- [Whoami](https://docs.together.ai/reference/cli/whoami.md): Show the project and organization for the API key used by the Together CLI.
- [Create a GPU cluster](https://docs.together.ai/reference/clusters-create.md): Create an Instant Cluster on Together's high-performance GPU clusters. With features like on-demand scaling, long-lived resizable high-bandwidth shared DC-local storage, Kubernetes and Slurm cluster flavors, a REST API, and Terraform support, you can run workloads flexibly without complex infrastruc…
- [Delete GPU cluster by cluster ID](https://docs.together.ai/reference/clusters-delete.md): Delete a GPU cluster by cluster ID.
- [Get GPU cluster by cluster ID](https://docs.together.ai/reference/clusters-get.md): Retrieve information about a specific GPU cluster.
- [List all GPU clusters](https://docs.together.ai/reference/clusters-list.md): List all GPU clusters.
- [List regions and corresponding supported driver versions](https://docs.together.ai/reference/clusters-list-regions.md)
- [Update a GPU cluster](https://docs.together.ai/reference/clusters-update.md): Update the configuration of an existing GPU cluster.
- [Create a shared volume](https://docs.together.ai/reference/clusters_storages-create.md): Instant Clusters supports long-lived, resizable in-DC shared storage with user data persistence. You can dynamically create and attach volumes to your cluster at cluster creation time, and resize as your data grows. All shared storage is backed by multi-NIC bare metal paths, ensuring high-throughput…
- [Delete a shared volume by ID](https://docs.together.ai/reference/clusters_storages-delete.md): Delete a shared volume. Note that if this volume is attached to a cluster, deleting will fail.
- [Get a shared volume by ID](https://docs.together.ai/reference/clusters_storages-get.md): Retrieve information about a specific shared volume.
- [List all shared volumes](https://docs.together.ai/reference/clusters_storages-list.md): List all shared volumes.
- [Update a shared volume](https://docs.together.ai/reference/clusters_storages-update.md): Update the configuration of an existing shared volume.
- [Create completion](https://docs.together.ai/reference/completions.md): Generate text completions for a given prompt using a language, code, or image model.
- [Create an evaluation job](https://docs.together.ai/reference/create-evaluation.md)
- [Create video](https://docs.together.ai/reference/create-videos.md): Create a video
- [Sprocket SDK reference](https://docs.together.ai/reference/dci-reference-sprocket.md): API reference for Sprocket classes, functions, and configuration.
- [Delete a file](https://docs.together.ai/reference/delete-files-id.md): Delete a previously uploaded data file.
- [Delete a fine-tune job](https://docs.together.ai/reference/delete-fine-tunes-id.md): Delete a fine-tuning job.
- [Create a new deployment](https://docs.together.ai/reference/deployments-create.md): Create a new deployment with specified configuration
- [Delete a deployment](https://docs.together.ai/reference/deployments-delete.md): Delete an existing deployment
- [Get a deployment by ID or name](https://docs.together.ai/reference/deployments-get.md): Retrieve details of a specific deployment by its ID or name
- [Get the list of deployments](https://docs.together.ai/reference/deployments-list.md): Get a list of all deployments in your project
- [Get logs for a deployment](https://docs.together.ai/reference/deployments-logs.md): Retrieve logs from a deployment, optionally filtered by replica ID.
- [Create a new secret](https://docs.together.ai/reference/deployments-secrets-create.md): Create a new secret to store sensitive configuration values
- [Delete a secret](https://docs.together.ai/reference/deployments-secrets-delete.md): Delete an existing secret
- [Get a secret by ID or name](https://docs.together.ai/reference/deployments-secrets-get.md): Retrieve details of a specific secret by its ID or name
- [Get the list of project secrets](https://docs.together.ai/reference/deployments-secrets-list.md): Retrieve all secrets in your project
- [Update a secret](https://docs.together.ai/reference/deployments-secrets-update.md): Update an existing secret's value or metadata
- [Download a file](https://docs.together.ai/reference/deployments-storage-get.md): Download a file by redirecting to a signed URL
- [Create a new volume](https://docs.together.ai/reference/deployments-storage-volumes-create.md): Create a new volume to preload files in deployments
- [Delete a volume](https://docs.together.ai/reference/deployments-storage-volumes-delete.md): Delete an existing volume
- [Get a volume by ID or name](https://docs.together.ai/reference/deployments-storage-volumes-get.md): Retrieve details of a specific volume by its ID or name
- [Get the list of project volumes](https://docs.together.ai/reference/deployments-storage-volumes-list.md): Retrieve all volumes in your project
- [Update a volume](https://docs.together.ai/reference/deployments-storage-volumes-update.md): Update an existing volume's configuration or contents
- [Update a deployment](https://docs.together.ai/reference/deployments-update.md): Update an existing deployment configuration
- [Create an A/B experiment](https://docs.together.ai/reference/dmi/ab-experiments-create.md): Creates a managed control/variant split across two to 20 deployments under the same endpoint. Exactly one member is the control, member percentages must add up to 100, and the split applies only to traffic that the endpoint would otherwise send to the control.
- [Delete an A/B experiment](https://docs.together.ai/reference/dmi/ab-experiments-delete.md): Deletes an A/B experiment and removes its managed traffic split. The deployments themselves are not deleted.
- [Get an A/B experiment](https://docs.together.ai/reference/dmi/ab-experiments-get.md): Retrieves an A/B experiment and its participating deployments, roles, and traffic percentages.
- [List A/B experiments](https://docs.together.ai/reference/dmi/ab-experiments-list.md): Lists the managed live-traffic experiments configured for an endpoint.
- [Update an A/B experiment](https://docs.together.ai/reference/dmi/ab-experiments-update.md): Updates an experiment's description or member traffic percentages. Use the experiment etag for optimistic concurrency.
- [Add a deployment adapter](https://docs.together.ai/reference/dmi/adapters-add.md): Attaches a LoRA adapter to a deployment. If the deployment is at adapter capacity, force can evict the oldest adapter.
- [Get a deployment adapter](https://docs.together.ai/reference/dmi/adapters-get.md): Gets an attached adapter and its per-cluster load state.
- [List deployment adapters](https://docs.together.ai/reference/dmi/adapters-list.md): Lists LoRA adapters attached to a deployment with per-cluster load state.
- [Remove a deployment adapter](https://docs.together.ai/reference/dmi/adapters-remove.md): Detaches an adapter from a deployment using its row-level etag for optimistic concurrency.
- [Update a deployment adapter](https://docs.together.ai/reference/dmi/adapters-update.md): Updates the pinned revision of an attached adapter using its row-level etag for optimistic concurrency.
- [Get a model configuration](https://docs.together.ai/reference/dmi/configs-get.md): Retrieves a model configuration revision by ID, including its runtime selectors and certifications.
- [List model configurations](https://docs.together.ai/reference/dmi/configs-list.md): Lists production-ready configuration revisions compatible with a reference model. Specify the model with `referenceModel` or the deprecated `referenceModelId`; if both are supplied, they must identify the same model. Results include public configurations and configurations owned by the specified pro…
- [Create a deployment](https://docs.together.ai/reference/dmi/deployments-create.md): Creates a model deployment under an endpoint. The deployment provisions asynchronously; monitor its status before routing live traffic to it.
- [Delete a deployment](https://docs.together.ai/reference/dmi/deployments-delete.md): Permanently deletes a deployment from its endpoint. Remove the deployment from live traffic first; use `etag` to reject the request if it changed after it was read.
- [Get a deployment](https://docs.together.ai/reference/dmi/deployments-get.md): Retrieves a deployment's desired configuration, placement, runtime information, and current provisioning status.
- [List deployments](https://docs.together.ai/reference/dmi/deployments-list.md): Lists the deployments attached to an endpoint, including their model, configuration, scaling settings, placement, and current status.
- [Update a deployment](https://docs.together.ai/reference/dmi/deployments-update.md): Updates mutable deployment fields such as its model, configuration, autoscaling bounds, or LoRA support. Changes that affect serving may trigger asynchronous reprovisioning.
- [Get endpoint analytics](https://docs.together.ai/reference/dmi/endpoints-analytics.md): Returns aggregated request, token, latency, throughput, error, and resource-utilization metrics for an endpoint over a time range. Optionally includes time-series buckets and a per-deployment breakdown.
- [Create an endpoint](https://docs.together.ai/reference/dmi/endpoints-create.md): Creates a stable, inference-addressable endpoint. Add one or more deployments and configure its traffic split before sending inference requests to the endpoint name.
- [Delete an endpoint](https://docs.together.ai/reference/dmi/endpoints-delete.md): Permanently deletes an endpoint. Delete its deployments first; use `etag` to reject the request if the endpoint changed after it was read.
- [Get an endpoint](https://docs.together.ai/reference/dmi/endpoints-get.md): Retrieves an endpoint and lightweight summaries of the deployments attached to it.
- [List endpoints](https://docs.together.ai/reference/dmi/endpoints-list.md): Lists the dedicated inference endpoints owned by the specified project.
- [List endpoint events](https://docs.together.ai/reference/dmi/endpoints-list-events.md): Lists an endpoint's audit and lifecycle events newest first. The feed combines endpoint changes with provisioning, scaling, readiness, rollout, and other events from deployments under the endpoint.
- [List organization endpoints](https://docs.together.ai/reference/dmi/endpoints-list-organization.md): Lists endpoints shared with every project in the specified organization. Project-private and public endpoints are not included.
- [Update an endpoint](https://docs.together.ai/reference/dmi/endpoints-update.md): Updates mutable endpoint fields such as its inference name, visibility, or deployment traffic split. Use `updateMask` to select fields explicitly and `etag` in the request body for optimistic concurrency.
- [Get an inference instance type](https://docs.together.ai/reference/dmi/instance-types-get.md): Retrieves the GPU resources, pricing, regional availability, and best-effort capacity headroom for one inference instance type.
- [List inference instance types](https://docs.together.ai/reference/dmi/instance-types-list.md): Lists hardware instance types currently available to inference deployments, including GPU resources, pricing, regions, and best-effort capacity headroom.
- [Create a remote model upload](https://docs.together.ai/reference/dmi/model-uploads-create.md): Starts an asynchronous job that imports model files from Hugging Face or a presigned URL into a registered model and creates a model revision when the import completes.
- [Get a remote model upload](https://docs.together.ai/reference/dmi/model-uploads-get.md): Retrieves the status, progress details, retry counts, and timestamps for a remote model import job.
- [List remote model uploads](https://docs.together.ai/reference/dmi/model-uploads-list.md): Lists asynchronous jobs that import model files from Hugging Face or a presigned remote URL.
- [List remote model upload events](https://docs.together.ai/reference/dmi/model-uploads-list-events.md): Lists progress and diagnostic events for a remote model import job.
- [Create a model](https://docs.together.ai/reference/dmi/models-create.md): Registers a custom model resource in the project. Registration creates the model's metadata; upload or import model files separately before deploying it.
- [Delete a model](https://docs.together.ai/reference/dmi/models-delete.md): Permanently deletes a custom model resource. The model must not be in use by an active deployment.
- [Get a model](https://docs.together.ai/reference/dmi/models-get.md): Retrieves a custom model's metadata, visibility, weight information, and base-model relationship.
- [List project models](https://docs.together.ai/reference/dmi/models-list.md): Lists custom model resources owned by the specified project. Use the organization endpoint to list models shared across projects or the supported-model catalog to discover Together-hosted base models.
- [List model files](https://docs.together.ai/reference/dmi/models-list-files.md): Lists files in the latest or specified revision of a model, including paths, sizes, and content hashes.
- [List organization models](https://docs.together.ai/reference/dmi/models-list-organization.md): Lists custom models shared with every project in the specified organization. Project-private and public models are not included.
- [List model revisions](https://docs.together.ai/reference/dmi/models-list-revisions.md): Lists the immutable file revisions available for a custom model, newest first.
- [Update a model](https://docs.together.ai/reference/dmi/models-update.md): Updates mutable model metadata such as its inference name, description, base model, or visibility.
- [Get a placement profile](https://docs.together.ai/reference/dmi/placement-profiles-get.md): Retrieves a reusable placement profile and its ordered region preferences.
- [List placement profiles](https://docs.together.ai/reference/dmi/placement-profiles-list.md): Lists reusable, project-visible placement policies that control the regions where deployments may be scheduled.
- [Create a shadow experiment target](https://docs.together.ai/reference/dmi/shadow-experiment-targets-create.md): Adds a deployment under the same endpoint as a target for mirrored requests.
- [Delete a shadow experiment target](https://docs.together.ai/reference/dmi/shadow-experiment-targets-delete.md): Removes a target from a shadow experiment without deleting the underlying deployment.
- [Get a shadow experiment target](https://docs.together.ai/reference/dmi/shadow-experiment-targets-get.md): Retrieves one target configured to receive mirrored requests from a shadow experiment.
- [List shadow experiment targets](https://docs.together.ai/reference/dmi/shadow-experiment-targets-list.md): Lists the deployments that receive mirrored requests from a shadow experiment.
- [Update a shadow experiment target](https://docs.together.ai/reference/dmi/shadow-experiment-targets-update.md): Updates a shadow target's name, deployment, or description. `updateMask` is required and must select at least one mutable field.
- [Create a shadow experiment](https://docs.together.ai/reference/dmi/shadow-experiments-create.md): Creates an experiment that mirrors a sampled portion of endpoint traffic to one or more target deployments without returning their responses to clients. Add a description with the update operation after creation.
- [Delete a shadow experiment](https://docs.together.ai/reference/dmi/shadow-experiments-delete.md): Deletes a shadow experiment and its target records. The underlying deployments are not deleted.
- [Get a shadow experiment](https://docs.together.ai/reference/dmi/shadow-experiments-get.md): Retrieves a shadow experiment, including its sampling strategy and target deployments.
- [List shadow experiments](https://docs.together.ai/reference/dmi/shadow-experiments-list.md): Lists experiments that mirror sampled endpoint traffic to target deployments without affecting client responses. Set `includeTargets=true` to include target details inline.
- [Update a shadow experiment](https://docs.together.ai/reference/dmi/shadow-experiments-update.md): Updates a shadow experiment's description or source sampling strategy. `updateMask` is required; source changes also require the current `etag` in the request body.
- [Get a supported model](https://docs.together.ai/reference/dmi/supported-models-get.md): Retrieves a Together-hosted base model and the certified model, configuration, hardware, and performance profiles available for deployment.
- [List supported models](https://docs.together.ai/reference/dmi/supported-models-list.md): Lists Together-hosted base models that can be deployed for dedicated inference, together with their capabilities and certified deployment profiles.
- [Create embedding](https://docs.together.ai/reference/embeddings.md): Generate vector embeddings for one or more text inputs. Returns numerical arrays representing semantic meaning, useful for search, classification, and retrieval.
- [Get evaluation job details](https://docs.together.ai/reference/get-evaluation.md)
- [Get evaluation job status and results](https://docs.together.ai/reference/get-evaluation-status.md)
- [List all files](https://docs.together.ai/reference/get-files.md): List the metadata for all uploaded data files.
- [Retrieve file metadata](https://docs.together.ai/reference/get-files-id.md): Retrieve the metadata for a single uploaded data file.
- [Get file contents](https://docs.together.ai/reference/get-files-id-content.md): Get the contents of a single uploaded data file.
- [List all jobs](https://docs.together.ai/reference/get-fine-tunes.md): List the metadata for all fine-tuning jobs. Returns a list of FinetuneResponseTruncated objects.
- [List job](https://docs.together.ai/reference/get-fine-tunes-id.md): List the metadata for a single fine-tuning job.
- [List checkpoints](https://docs.together.ai/reference/get-fine-tunes-id-checkpoint.md): List the checkpoints for a single fine-tuning job.
- [List job events](https://docs.together.ai/reference/get-fine-tunes-id-events.md): List the events for a single fine-tuning job.
- [Get metrics](https://docs.together.ai/reference/get-fine-tunes-id-metrics.md): Retrieves recorded training metrics for a fine-tuning job in chronological order. All query parameters are optional: omit them to retrieve all metrics.
- [Get model limits](https://docs.together.ai/reference/get-fine-tunes-models-limits.md): Get model limits for a specific fine-tuning model.
- [Download model](https://docs.together.ai/reference/get-finetune-download.md): Receive a compressed fine-tuned model or checkpoint.
- [Fetch video metadata](https://docs.together.ai/reference/get-videos-id.md): Fetch video metadata
- [Get model list](https://docs.together.ai/reference/list-evaluation-models.md)
- [Get all evaluation jobs](https://docs.together.ai/reference/list-evaluations.md)
- [Create job](https://docs.together.ai/reference/post-fine-tunes.md): Create a fine-tuning job with the provided model and training data.
- [Estimate price](https://docs.together.ai/reference/post-fine-tunes-estimate-price.md): Estimate the price of a fine-tuning job.
- [Cancel job](https://docs.together.ai/reference/post-fine-tunes-id-cancel.md): Cancel a currently running fine-tuning job. Returns a FinetuneResponseTruncated object.
- [Create image](https://docs.together.ai/reference/post-images-generations.md): Use an image model to generate an image for a given prompt.
- [Cancel a queued job](https://docs.together.ai/reference/queue-cancel.md): Cancel a pending job. Only jobs in pending status can be canceled. Running jobs cannot be stopped. Returns the job status after the attempt. If the job is not pending, returns 409 with the current status unchanged.
- [Get queue metrics](https://docs.together.ai/reference/queue-metrics.md): Get the current queue statistics for a model, including pending and running job counts.
- [Get job status](https://docs.together.ai/reference/queue-status.md): Poll the current status of a previously submitted job. Provide the request_id and model as query parameters.
- [Submit a queued job](https://docs.together.ai/reference/queue-submit.md): Submit a new job to the queue for asynchronous processing. Jobs are processed in strict priority order (higher priority first, FIFO within the same priority). Returns a request ID that can be used to poll status or cancel the job.
- [Remediation approve](https://docs.together.ai/reference/remediation-approve.md): Approves a pending remediation.
- [Remediation cancel](https://docs.together.ai/reference/remediation-cancel.md): Cancels a pending remediation.
- [Remediation create](https://docs.together.ai/reference/remediation-create.md): Creates a new remediation for an instance.
- [Remediation get](https://docs.together.ai/reference/remediation-get.md): Retrieve the status of a specific remdiation on a specific instance in a specific cluster.
- [Remediation list](https://docs.together.ai/reference/remediation-list.md)
- [Remediation reject](https://docs.together.ai/reference/remediation-reject.md): Rejects a pending remediation.
- [Create a rerank request](https://docs.together.ai/reference/rerank.md): Rerank a list of documents by relevance to a query. Returns a relevance score and ordering index for each document.
- [Execute code](https://docs.together.ai/reference/tci-execute.md): Executes the given code snippet and returns the output. Without a session_id, a new session is created to run the code. If you pass a valid session_id, the code runs in that session. This is useful for running multiple code snippets in the same environment, because dependencies and similar things ar…
- [List active sessions](https://docs.together.ai/reference/tci-sessions.md): Lists all your currently active sessions.
- [Upload a file](https://docs.together.ai/reference/upload-file.md): Upload a file with specified purpose, file name, and file type.
- [Get API key identity](https://docs.together.ai/reference/whoami.md): Returns identity information about the authenticated API key. Useful for confirming which project and organization a key is scoped to, and for obtaining the project slug used to compose the `model` value (`<project_slug>/<endpoint_slug>`) in dedicated endpoint inference calls. Requires a Bearer API…
- [TypeScript Library](https://docs.together.ai/typescript-library.md)

## OpenAPI Specs

- [openapi](https://docs.together.ai/openapi.yaml)
- [tcloud](https://docs.together.ai/tcloud.yaml)
- [deprecated-spec](https://docs.together.ai/deprecated-spec.json)