Together Inference

NewVerified

Run open-source LLMs with fast, scalable inference API

8.1 (53.155 score)

freemiumAPI Available

Overview

Together provides a managed inference platform for deploying open-source language models at scale. Developers and enterprises use it to avoid vendor lock-in while accessing competitive pricing and performance. The platform supports hundreds of models and offers both API and dedicated instance options.

Pros

Access 100+ open-source models without switching providers
Pay-as-you-go pricing undercuts closed model APIs significantly
Dedicated clusters available for consistent, predictable latency
Simple API compatible with OpenAI client libraries
Supports fine-tuning on your own proprietary data

✕ Cons

Open-source model outputs often lag proprietary alternatives
No built-in safety guardrails compared to major providers
Smaller community and fewer integrations than established platforms

Key Features

Multi-model inference API

Model fine-tuning service

Dedicated inference clusters

Batch processing jobs

OpenAI API compatibility

Prompt caching

Use Cases

AI startups seeking cost-effective inference without vendor lock-inEnterprises deploying proprietary models with fine-tuningResearchers experimenting with multiple open-source language modelsDevelopers building chatbots and text generation applications

Best For

Machine Learning EngineersBackend DevelopersStartups & Indie HackersAI Application BuildersData Scientists

Frequently Asked Questions

What is the pricing model for Together Inference?▾

Together Inference uses pay-as-you-go pricing based on tokens consumed, with competitive rates compared to other inference providers. Pricing varies by model and inference type (real-time vs. batch).

How steep is the learning curve for getting started?▾

Setup is straightforward with good documentation and a simple API. Developers familiar with REST APIs or Python SDKs can integrate it within hours.

What integrations and APIs does Together Inference offer?▾

It provides REST APIs, Python and JavaScript SDKs, and supports integration with popular frameworks. The platform also offers batch processing APIs for large-scale inference jobs.

What are the main limitations of Together Inference?▾

The platform is limited to open-source models only, which may not include proprietary models like GPT-4. Custom model deployment options are more limited compared to full ML platforms.

What is Together Inference best used for?▾

It's ideal for projects requiring fast, cost-effective inference with open-source models, such as building applications with Llama, Mistral, or other community models, and handling batch processing workloads.