Together AI Endpoints

NewVerified

Run open-source LLMs and custom models at scale

8.3 (64.23 score)

paidAPI Available

Overview

Together AI provides managed API endpoints for running open-source language models and fine-tuned custom models in production. It's designed for developers and teams who need flexible, cost-effective alternatives to closed-source APIs with full control over model selection and deployment. The platform handles infrastructure scaling automatically while offering competitive pricing per token.

Pros

Supports 100+ open-source models with single API
Fine-tune models on your own data and deploy immediately
Pay-per-token pricing without minimum commitments
Lower latency through optimized inference infrastructure
Full control over model selection and parameters

✕ Cons

No free tier to test before committing spend
Smaller model library compared to major cloud providers
Limited enterprise support at lower pricing tiers

Key Features

Multi-model API endpoint

Fine-tuning interface

Batch processing

Custom model deployment

Real-time inference

Token-based pricing

Use Cases

Startups deploying cost-sensitive LLM applications avoiding vendor lock-inML teams fine-tuning models for domain-specific tasksCompanies running private models with sensitive data requirementsResearchers experimenting with multiple open-source model architectures

Best For

ML EngineersStartups & Scale-upsOpen-Source AdvocatesHigh-Volume API UsersFine-Tuning Projects

Frequently Asked Questions

What is the pricing model for Together AI Endpoints?▾

Together AI Endpoints uses pay-as-you-go pricing based on tokens consumed, with competitive rates compared to other LLM providers. Pricing varies by model and inference type (standard vs. streaming).

How difficult is it to get started with Together AI Endpoints?▾

Setup is straightforward—you get an API key and can make requests immediately using their REST API or Python SDK. Most developers can integrate it within minutes with basic API knowledge.

Does Together AI Endpoints support integrations or have an API?▾

Yes, it offers a comprehensive REST API and Python SDK, plus integrations with LangChain and other LLM frameworks, making it easy to embed into existing applications.

What are the main limitations of Together AI Endpoints?▾

Context window sizes vary by model, and while fine-tuning is available, it requires additional setup and cost. Availability of the latest proprietary models is limited compared to OpenAI.

What is the ideal use case for Together AI Endpoints?▾

It's ideal for teams wanting cost-effective inference at scale, those needing low-latency responses, or projects requiring fine-tuned open-source models without vendor lock-in.