About Together AI
Together AI is a comprehensive, research-driven platform designed specifically for the needs of AI-native companies and developers. At its core, it provides an infrastructure referred to as the AI Native Cloud, which aims to streamline the entire generative AI lifecycle, including training, fine-tuning, and production-scale inference. By leveraging frontier research, the platform allows users to interact with a library of open-source models—such as Llama, DeepSeek, Mistral, and Qwen—through OpenAI-compatible APIs, providing an alternative to closed-model ecosystems.
The platform architecture is built for performance and operational reliability. It offers serverless inference for text, vision, image, and video models, alongside dedicated endpoints for requirements involving guaranteed performance and custom model support. For large-scale workloads, the service provides GPU clusters ranging from instant, self-service H100 instances to large-scale Frontier AI Factories designed for up to 100,000 NVIDIA GPUs. These clusters utilize high-speed interconnects like NVIDIA InfiniBand and NVLink, which are utilized to minimize latency during distributed training and inference tasks.
This infrastructure is intended for developers, machine learning researchers, and enterprises requiring high-performance compute without vendor lock-in. It is used by organizations that prioritize open-source transparency and data privacy. Current implementations include companies like Hedra and Cursor, as well as researchers at Salesforce, who utilize the platform to manage inference latency and operational costs. The system is built to handle trillions of tokens with consistent performance at production scales.
A defining characteristic of the platform is its integration with industry-standard AI research. The team behind the tool has contributed to technical advancements such as FlashAttention and the RedPajama datasets. This research background is applied to the platform's performance metrics, which include reported increases in inference and training speeds compared to standard frameworks. Additionally, the service ensures that users retain ownership of their fine-tuned models, allowing for greater flexibility in terms of data residency and provider choice.
Together AI FAQs
Which models are available through the Serverless Inference API?
Together AI supports a wide array of open-source models including Llama 3.3, DeepSeek-V3, Mistral Small, Qwen3, and GLM-5. It also provides access to specialized models for image generation like FLUX.1 and video models like MiniMax Hailuo.
How does the platform ensure there is no vendor lock-in?
The platform focuses on open-source standards and guarantees that users own the models they fine-tune. This allows organizations to migrate their models to other providers or local environments at any time without being restricted by proprietary formats.
What kind of performance improvements can I expect for inference?
The platform utilizes research-backed accelerators like ATLAS to deliver up to 3.5x faster inference for top open-source models. Customers like Salesforce have reported a 2x reduction in time-to-first-token latency.
Does Together AI support custom model fine-tuning?
Yes, the platform supports both Supervised Fine-Tuning and Direct Preference Optimization (DPO). Users can choose between LoRA for efficiency or Full Fine-Tuning for maximum model customization across various model sizes.
What security and moderation tools are available?
Together AI provides integrated moderation models such as Llama Guard 3 and VirtueGuard. These models allow developers to filter and classify text and vision content for safety and compliance directly through the API.
