Together AI
The platform for building open and custom AI.
Overview
Together AI is a cloud platform that makes it easy to build and run generative AI models. They offer a wide selection of open-source models that can be run on their fast inference engine. Together AI also provides tools for fine-tuning and customizing models, as well as a serverless API for easy integration.
✨ Key Features
- Large library of open-source models
- Fast inference engine
- Serverless API
- Fine-tuning capabilities
- Custom model training
🎯 Key Differentiators
- Focus on speed and performance of inference
- Large selection of open-source models
- Cost-effective pricing
Unique Value: A fast, easy, and cost-effective way to run and customize the best open-source generative AI models.
🎯 Use Cases (4)
✅ Best For
- Serving open-source models with low latency
- Cost-effective fine-tuning of models
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Users who exclusively want to use proprietary, closed-source models
🏆 Alternatives
Offers a more streamlined and performant experience for running open-source models compared to general-purpose cloud providers.
💻 Platforms
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Live Chat
- ✓ Dedicated Support (Enterprise tier)
🔒 Compliance & Security
💰 Pricing
✓ 14-day free trial
Free tier: Free credits upon signup.
🔄 Similar Tools in LLM API Providers
OpenAI
A research and deployment company that aims to ensure that artificial general intelligence benefits ...
Google Vertex AI
A unified MLOps platform to help customers build, deploy, and scale machine learning models....
Amazon Bedrock
A fully managed service that offers a choice of high-performing foundation models from leading AI co...
Anthropic
An AI safety and research company focused on developing helpful, harmless, and honest AI systems....
Cohere
An AI platform for enterprises, providing access to advanced large language models and RAG capabilit...
Hugging Face
A platform that provides tools for building, training, and deploying state-of-the-art machine learni...