In the field of artificial intelligence, Together AI recently announced a round of round B financing of up to $305 million, and the news quickly attracted widespread attention from the industry. The company's rapid rise is closely related to its latest in-depth reasoning model, DeepSeek-R1. Contrary to initial concerns, many industry experts believe that advances in deep reasoning technology are not only not reducing the demand for infrastructure, but are constantly increasing this demand.
Since its inception in 2023, Together AI’s mission is to simplify enterprise use of open source large language models (LLMs). Over time, the company gradually expanded its platform to launch a solution called "Together Platform" that supports deployment of AI in virtual private clouds and on-premises environments. In 2025, Together AI further enhanced its platform capabilities and launched its inference clustering and autonomous intelligence (Agentic AI) capabilities.
According to Vipul Prakash, CEO of Together AI, the parameters of DeepSeek-R1 are as high as 671 billion, which makes the cost of operating inference not to be underestimated. To meet the needs of more and more users, Together AI has launched the "Inference Cluster" service, providing customers with dedicated computing power from 128 to 2,000 chips to ensure the best performance of the model. In addition, DeepSeek-R1 request processing times are usually longer, with an average of two to three minutes, which also leads to an increase in infrastructure demand.
In terms of the application of inference models, Together AI has seen some specific usage scenarios, such as coding agents, reducing the illusion of the model, and achieving self-improvement of the model through reinforcement learning. These applications not only improve work efficiency, but also improve the accuracy of model output.
In addition, Together AI has acquired CodeSandbox to enhance its capabilities in autonomous intelligent workflows. This acquisition allows it to execute code quickly in the cloud, reducing latency and improving the performance of proxy workflows.
Faced with fierce market competition, Together AI's infrastructure platform is constantly being optimized, and the deployment of its new generation of Nvidia Blackwell chips will provide higher performance and lower latency for model training and inference. Prakash pointed out that compared with other platforms such as Azure, Together AI's inference speed has significantly improved, greatly meeting customers' needs for high-performance AI infrastructure.
Key points:
Together AI received US$305 million in financing to promote the development of in-depth reasoning models.
The complexity of DeepSeek-R1 has significantly increased infrastructure demand, and the launch of "inference cluster" service is launched to meet market demand.
The newly acquired CodeSandbox and Nvidia Blackwell chips will further enhance the market competitiveness of Together AI.