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Gulf Press > Technology > Sources: Project SGLang spins out as RadixArk with $400M valuation as inference market explodes
Technology

Sources: Project SGLang spins out as RadixArk with $400M valuation as inference market explodes

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Last updated: 2026/01/22 at 10:04 AM
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A growing trend in the artificial intelligence landscape sees open-source projects rapidly evolving into venture-backed companies, attracting significant investment. The latest example is RadixArk, the commercial entity behind SGLang, a tool designed to accelerate and reduce the cost of running AI models. This development highlights the increasing demand for efficient AI infrastructure and the commercial potential within the open-source AI community.

RadixArk recently achieved a valuation of approximately $400 million in a funding round led by Accel, according to sources familiar with the matter. The company, launched in August 2023, originated from research conducted within the UC Berkeley lab of Databricks co-founder Ion Stoica. This swift transition from academic project to high-valuation startup underscores the rapid pace of innovation in the AI sector.

The Rise of AI Inference Optimization

Both SGLang and its commercial counterpart, RadixArk, concentrate on optimizing AI inference processing. Inference, the process of using a trained model to make predictions, represents a substantial portion of the operational costs associated with AI services. By improving efficiency, these tools can deliver immediate and significant cost savings for businesses deploying AI applications.

Ying Sheng, a former engineer at xAI and a key contributor to SGLang, now serves as the co-founder and CEO of RadixArk. Her move signals a broader trend of talent transitioning from established AI companies to build independent ventures focused on foundational AI technologies. RadixArk has also secured angel investment from prominent figures like Intel CEO Lip-Bu Tan.

From Open Source to Startup

RadixArk isn’t an isolated case. vLLM, another project focused on optimizing inference, is reportedly in discussions to raise $160 million at a $1 billion valuation, with Andreessen Horowitz potentially leading the investment. However, vLLM co-founder Simon Mo has characterized reports of the funding round as “factually inaccurate” without providing specifics.

Like SGLang, vLLM was also incubated in Ion Stoica’s UC Berkeley lab, demonstrating the lab’s role as a breeding ground for innovative AI technologies. Several major tech companies are already utilizing vLLM for their inference workloads, indicating the growing adoption of these optimization tools.

Additionally, RadixArk continues to develop SGLang as an open-source project while simultaneously building Miles, a framework specifically designed for reinforcement learning. This dual approach allows the company to maintain a community presence while also offering commercial services.

Growing Investment in AI Infrastructure

While many of RadixArk’s core tools remain freely available, the company has begun charging fees for hosting services, according to sources. This move towards monetization is a common step for startups transitioning from open-source projects to commercial entities.

The surge in funding for companies providing AI infrastructure is indicative of the broader market demand. Baseten recently secured $300 million at a $5 billion valuation, and Fireworks AI raised $250 million at a $4 billion valuation last year. These investments demonstrate the critical importance of the infrastructure layer in supporting the growth of AI applications.

Brittany Walker, a general partner at CRV, noted the increasing popularity of both SGLang and vLLM over the past six months, highlighting the growing recognition of their value within the AI community. This increased recognition is driving both adoption and investment.

The trend of open-source AI tools attracting substantial venture capital is likely to continue as the demand for efficient and cost-effective AI solutions grows. The next few months will be crucial for RadixArk and vLLM as they navigate their respective funding rounds and scale their operations. Monitoring their progress, as well as the emergence of new players in the machine learning infrastructure space, will be key to understanding the future of AI deployment. The final details of the vLLM funding round, and RadixArk’s expansion of its commercial offerings, remain key areas to watch.

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