Magic, a prominent AI startup specializing in code generation and software development automation, has successfully closed a substantial $320 million funding round. The investment, disclosed in a blog post on Thursday, features contributions from notable figures and organizations, including former Google CEO Eric Schmidt, Alphabet’s CapitalG, Atlassian, Elad Gil, Jane Street, Nat Friedman, Daniel Gross, and Sequoia.
This latest funding boosts Magic’s total capital raised to nearly $465 million, placing it among the top-funded AI coding startups alongside peers like Codeium, Cognition, Poolside, Anysphere, and Augment—interestingly, Schmidt is also an investor in Augment.
In July, Reuters reported Magic’s ambition to secure over $200 million at a valuation of $1.5 billion. While the exact current valuation remains undisclosed, Magic was valued at $500 million in February, indicating that this funding round exceeded initial expectations.
Additionally, Magic has announced a strategic partnership with Google Cloud to develop two advanced “supercomputers” on the Google Cloud Platform. The planned infrastructure includes the Magic-G4, featuring Nvidia H100 GPUs, and the upcoming Magic-G5, which will utilize Nvidia’s next-generation Blackwell chips scheduled for release next year. These GPUs, known for their parallel processing capabilities, are essential for training and deploying generative AI models.
Magic aims to scale the Magic-G5 cluster to “tens of thousands” of GPUs, targeting a combined computational power of 160 exaflops—equivalent to one quintillion operations per second.
Eric Steinberger, co-founder and CEO of Magic, expressed enthusiasm about the partnership, stating, “We are excited to partner with Google and Nvidia to build our next-gen AI supercomputer on Google Cloud. Nvidia’s Blackwell system will significantly enhance the efficiency of our models, and Google Cloud provides the optimal platform for rapid scaling and a robust suite of cloud services.”
Steinberger, alongside Sebastian De Ro, co-founded Magic in 2022. Reflecting on his early interest in AI, Steinberger previously shared with TechCrunch that his fascination began in high school, where he and his peers set up their school’s computers for machine-learning training.
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