# Together AI An AI cloud platform for teams building, tuning, and deploying open-source models. - Findings24: - Site: - Preços: Paid - Categorias: Plataformas de inferência de IA, Implantação de modelos de IA, Nuvem de GPU ## O que é Together AI? Together AI is a full-stack AI cloud platform for developing and operating applications with open-source models. It brings together model inference, fine-tuning, GPU compute, and supporting infrastructure, so teams can move from experimentation to deployed workloads within one platform. Inference options range from on-demand serverless access to reserved throughput and dedicated deployments; compute includes GPU clusters, while model shaping supports fine-tuning. The platform also offers managed storage and code sandboxes. Together Research works on production-oriented inference systems, GPU kernels, model shaping, and agents, informing the platform’s focus on AI workloads. ## O que Together AI pode fazer? ### Multiple inference deployment options Run models through serverless inference, asynchronous batch processing, provisioned throughput, or dedicated model infrastructure. These options support different workload patterns, from on-demand requests to reserved capacity and dedicated hardware. ### Fine-tuning for open-source models Fine-tune models for production workloads using supervised fine-tuning and direct preference optimization. Together AI describes fine-tuning as a way to adjust model accuracy and behavior without managing training infrastructure. ### GPU clusters and accelerated compute Provision GPU capacity from self-serve clusters to larger deployments. Together AI also offers its Kernel Collection as an optimization layer for compute workloads. ### Infrastructure for generative media Dedicated container inference is designed for deploying video, audio, and image models on GPU infrastructure, with performance acceleration from Together Research. ### Developer and data infrastructure Code sandboxes provide environments for AI applications and agents, including a code-interpreter API. Managed storage includes object storage and parallel filesystems for AI workloads. ## Casos de uso ### Build and test AI applications Use serverless model inference to evaluate available open-source models and connect model capabilities to an application without first managing serving infrastructure. ### Process large asynchronous workloads Submit batch inference jobs for high-volume processing when results do not need to be returned interactively. The service supports serverless models and private deployments. ### Operate production model services Choose provisioned throughput for reserved capacity and token-based pricing, or dedicated inference when workloads call for dedicated hardware, custom models, and autoscaling. ### Adapt a model to a specialized task Fine-tune an open-source model with supervised fine-tuning or direct preference optimization to shape its behavior for a production workflow. ### Develop real-time voice agents Combine speech-to-text, language models, and text-to-speech through the voice offering. Its model library and shared API let teams switch voice pipeline models without rebuilding integrations. ## Perguntas frequentes ### What can I use Together AI for? The platform supports model inference, fine-tuning, GPU compute, code sandboxes, and managed storage. It also provides a voice solution for building real-time voice agents. ### How can I deploy a model? Options include serverless inference, batch inference, provisioned throughput, dedicated model inference, and dedicated container inference. The right option depends on whether the workload is asynchronous, needs reserved capacity, or calls for dedicated infrastructure. ### Can I fine-tune models without managing training infrastructure? Together AI offers fine-tuning for open-source models and lists supervised fine-tuning and direct preference optimization as available methods. Its product description says training infrastructure does not need to be managed by the user. ### How is usage priced? Pricing varies by service: serverless models are listed with per-token rates, media models use units such as images, video, characters, or audio minutes, and GPU or sandbox resources have usage-based rates. Some dedicated and reserved options direct customers to contact sales. ## Informações rápidas - **Product category**: AI cloud and developer platform - **Core services**: Inference, fine-tuning, GPU clusters, sandboxes, and managed storage - **Model coverage**: Open-source models across text, image, video, code, and voice - **Pricing model**: Usage-based rates vary by model and service; some capacity options require contacting sales - **Website**: together.ai