Skip to main content
TA

Together AI

Production infrastructure for open-source model inference and training

Together AI is a cloud platform for running, fine-tuning, and deploying open-source AI models. It is aimed at developers and teams that need model inference, GPU compute, storage, and training infrastructure in one place.

iOS
API
B2B
Cloud Hosted
Hybrid
Model Agnostic
Supports Local Models
Visit Together AI

Is this your tool? Claim this listing to manage your content and analytics.

Ask about Together AI

Get answers based on Together AI's actual documentation

Try asking:

About

What It Is

Together AI is a cloud platform for working with open-source AI models in production. According to its product pages, it covers serverless inference, batch inference, dedicated inference, GPU clusters, managed storage, sandboxed development environments, and fine-tuning. The target audience appears to be developers and ML teams building AI applications and infrastructure, especially those working with open-source models.

You typically get started through Together AI’s hosted platform and APIs, with documentation linked from each product area. The platform is positioned around model serving and compute rather than an end-user chatbot, so it is more of a developer infrastructure layer than an AI assistant.

What to Know

The platform is strongest as infrastructure for inference and model operations: it is built for production workloads, scales from serverless usage to dedicated deployments, and supports batch processing and GPU-backed compute. That said, it is not primarily an autonomous agent product. Based on the content provided, it does not appear to manage multi-step tasks on your behalf in the way a general-purpose agent does.

Pricing details were not fully available in the crawled content, aside from a pricing page and a prompt to contact sales for help choosing. The pages also do not clearly state the underlying model provider strategy beyond support for open-source models, nor do they mention MCP support or open-source licensing for the platform itself. If you need a consumer app, chat-first assistant, or a local/on-device tool, this is probably not the right fit.

Key Features
Serverless inference for open-source models
Batch inference for asynchronous large-scale workloads
Dedicated model inference on reserved infrastructure
Dedicated container inference for video, audio, and image models
GPU clusters for scalable compute
Use Cases
Serving open-source LLMs in production through an API
Running batch inference jobs over large token volumes
Deploying dedicated endpoints for latency-sensitive applications
Agenticness: Guided Assistant 💬

Executes tasks you assign, one step at a time, within narrow domains.

High evidence
Last evaluated: Apr 1, 2026
This tool has strong action capabilities but limited safety controls. Use with appropriate oversight.

Dimension Breakdown

Action Capability
Autonomy
Adaptation
State & Memory
Safety

Categories

Pricing

Pricing not publicly available in the crawled content. The pricing page indicates serverless inference, dedicated inference, GPU clusters, sandbox, managed storage, and fine-tuning, and includes a contact sales option.

Details
AddedApril 1, 2026
RefreshedApril 1, 2026
Quick Facts
DeploymentCloud-hosted
AutonomyCopilot (human-in-loop)
Model supportMulti-model
Open sourceNo
Team supportEnterprise
Pricing modelUsage-based
Interfaceapi, gui
Sources
Similar tools

Related Tools

Anyscale is a fully managed Ray platform that removes the infrastructure work from building and deploying AI applications. It helps teams run Ray jobs, services, and workflows with autoscaling, monitoring, and API-driven cluster management.

Paid
iOS
API
+4

GroqCloud is an AI inference platform for developers that focuses on low latency and predictable spend. It provides API access to text, audio, vision, and image-to-text models, with free, developer, and enterprise plans.

iOS
API
For Developers
+4

Fireworks AI is a model hosting and inference platform for teams building with open and proprietary models. It covers serverless inference, fine-tuning, embeddings, speech-to-text, and on-demand GPU deployments.

Paid
Enterprise
iOS
+4

Replicate lets you run and fine-tune models, and deploy custom models through an API. It’s aimed at developers who want to add image, speech, music, video, or LLM capabilities without managing model hosting themselves.

iOS
API
Vision
+4