A pattern is emerging in the AI infrastructure world: popular open source tools are turning into venture-backed startups worth hundreds of millions of dollars. The latest example is RadixArk, the commercial company behind SGLang, an increasingly popular tool that helps AI models run faster and cheaper.
RadixArk was recently valued at about $400 million in a funding round led by Accel, according to two people familiar with the matter, a remarkable amount for a startup that was only announced last August. TechCrunch could not confirm the size of the funding.
The news comes as some of the team responsible for maintaining SGLang, which is used by companies like xAI and Cursor to accelerate AI model training, have moved to the recently launched commercial startup. RadixArk originated as SGLang in 2023 inside the UC Berkeley lab of Databricks co-founder Ion Stoica.
The startup previously raised angel capital from investors including Intel CEO Lip-Bu Tan, the people said.
Ying Sheng, a key contributor to SGLang and a former engineer at xAI, left Elon Musk’s AI startup to become the co-founder and CEO of RadixArk, according to a LinkedIn announcement she made last month. Sheng was previously a researcher at Databricks.
RadixArk’s Ying Sheng, Accel and Lip-Bu Tan did not respond to a request for comment.
Both SGLang and RadixArk focus on optimizing inference processing—essentially allowing models to run faster and more efficiently on the same hardware. Along with model training, inference represents a large portion of the server costs associated with AI services. As a result, tools that optimize the process can create huge savings almost immediately.
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RadixArk is not alone in making this transition from open source project to well-funded startup. vLLM, a more mature inference optimization project, has also taken the plunge. The fledgling company has been in talks to raise up to $160 million in funding at a valuation of about $1 billion, Forbes reported last month.
Three people familiar with that deal tell TechCrunch that Andreessen Horowitz is leading the investment in vLLM, though final numbers for that investment are yet to be seen. Andreessen Horowitz declined to comment. vLLM co-founder Simon Mo characterized the information about this round as “factually inaccurate” in a statement to TechCrunch, though he declined to specify which details were incorrect.
Like SGLang, vLLM was incubated in Ion Stoica’s lab at UC Berkeley. Stoica, a professor at UC Berkeley, is the famous co-founder of Databricks as well as a number of other startups.
Several large tech companies are already running their inference workloads using vLLM, and SGLang has also gained significant popularity over the past six months, Brittany Walker, a general partner at CRV, told TechCrunch. Her company did not endorse either company.
RadixArk continues to develop SGLang as an open source AI modeling engine. The startup is also building Miles, a specialized framework designed for reinforcement learning that allows companies to train AI models to get smarter over time.
While most of its tools remain free, RadixArk has begun charging fees for hosting services, a person familiar with the company told TechCrunch.
Startups that provide inference infrastructure for developers have seen an increase in funding in recent months, underscoring the continued importance of the inference layer to AI. Baseten recently secured $300 million at a $5 billion valuation, The Wall Street Journal reported Tuesday. This follows a similar move by rival Fireworks AI, which raised $250 million at a $4 billion valuation last October.