Together AI
Build, deploy, and optimize AI models with ultra-fast, scalable solutions.
What is Together AI?
Key Features
Access to open-source models
Run popular models like Llama, Mistral, and others without licensing restrictions
Fine-tuning tools
Customise models on your own data using the platform's training infrastructure
Inference API
Deploy models with low latency and high throughput for production applications
Distributed computing
use multiple GPUs and hardware configurations for faster processing
Model management
Version control, monitoring, and performance tracking for deployed models
Cost monitoring
Transparent pricing and usage analytics to track spending
Pros & Cons
Advantages
- Open-source focus means no vendor lock-in; you're working with freely available models
- Generally more affordable than proprietary model APIs for high-volume inference
- Flexible infrastructure lets you choose hardware configurations suited to your workload
- Good option for teams wanting fine-grained control over their models and data
Limitations
- Requires more technical knowledge than simple chat interfaces; you'll need familiarity with APIs and model deployment
- Performance and reliability depend on your own infrastructure choices and configuration decisions
- Smaller community and ecosystem compared to larger cloud providers
Use Cases
Fine-tuning open-source models on proprietary datasets for specialise tasks
Running inference at scale for chatbots, content generation, or classification systems
Building applications where data privacy is important and you want models running in your own environment
Experimenting with different model architectures and comparing their performance and cost
Cost-conscious production deployments where open-source models meet your performance requirements
Pricing
Access to open-source models and basic tools; pay only for compute resources used
Quick Info
- Website
- www.together.ai
- Pricing
- Open Source
- Platforms
- Web, API
- Categories
- Research, Image Generation, Productivity