Together AI Features

ATLAS - Accelerate Your AI Development

Experience runtime-learning accelerators that deliver up to 4x faster LLM inference. ATLAS is designed specifically for AI-native developers, allowing real-time adaptation of models which is critical for those operating in fast-paced environments. By implementing ATLAS, you can significantly decrease the time-to-market for your AI applications, enabling quicker iterations and enhanced user feedback loops. This swift responsiveness not only accelerates development timelines but also optimizes end-user experiences, giving you a competitive advantage in your industry.

Together Instant Clusters - On-Demand GPU Resources

Unlock the power of self-service NVIDIA GPUs with Together Instant Clusters, now generally available for developers and teams. This feature streamlines the process of accessing powerful computational resources, eliminating the lengthy procurement phases typically associated with GPU access. Instant Clusters provide a virtualized environment that scales effortlessly according to demand, ensuring that your AI workloads run efficiently without the overhead costs of maintaining physical hardware. For founders looking to innovate quickly, this offers a flexible and agile solution to enhance their R&D efforts.

Batch Inference API - Cost-Effective Model Processing

With our Batch Inference API, process billions of tokens at a 50% lower cost across most models, making it an essential tool for efficient data handling and analytics. This feature is particularly advantageous for teams who are working with extensive datasets or looking to optimize their AI projects' financial footprint. By reducing the costs associated with token processing, teams can allocate resources more effectively, allowing for reinvestment in other critical areas of development, such as research or user experience enhancements. This not only supports better budget management but also ensures high-quality outcomes from your AI models.

Fine-Tuning Platform Upgrades - Enhanced Model Customization

Take advantage of our upgraded Fine-Tuning Platform which accommodates larger models and longer contexts, facilitating a more refined approach to model customization. This differentiation empowers developers to fine-tune their models to meet the specific demands of their applications, enhancing relevance and accuracy in outputs. This capability is vital for organizations that require tailored solutions that can adapt to rapidly changing user needs or unique market conditions. By employing larger models, your AI can derive deeper insights and produce more nuanced responses, significantly improving user satisfaction.

Performance-Optimized GPU Clusters - Unmatched Scalability

Our performance-optimized GPU clusters are built for reliability and speed at production scale. This infrastructure is capable of processing trillions of tokens in just a matter of hours, ensuring your applications are primed for rapid launches without sacrificing quality or performance. Companies that incorporate this technology experience enhanced throughput and can scale their operations seamlessly as demand fluctuates. This level of scalability is crucial for those in growth phases or seasonal markets, allowing for sustained performance regardless of volume shifts in usage.

Industry-Leading Unit Economics - Maximize Your ROI

The Together AI Platform is designed to continuously optimize performance across both inference and training stages, delivering not only superior outputs but also industry-leading unit economics. This focus on efficiency means that teams can effectively reduce the total cost of ownership (TCO) for AI operations, making it easier to scale projects without proportional increases in expenditure. For startups and enterprises alike, understanding and leveraging these economics fosters a more sustainable growth trajectory and allows for informed strategic decisions regarding resource allocation and future investments in technology.