Fireworks AI Secures $250M Series C at $4 Billion Valuation, Processes 10 Trillion Tokens Daily

Redwood City, California – Fireworks AI, a leading AI inference cloud provider, today announced it has closed a $250 million Series C funding round, elevating its valuation to $4 billion. The round was co-led by Lightspeed Venture Partners, Index Ventures, and Evantic, with continued participation from existing investor Sequoia Capital, bringing Fireworks AI's total funding to $327 million. The investment will fuel global expansion, advanced algorithm development, and hiring across engineering and go-to-market teams.

Lightspeed Partners announced their co-leadership in the funding round via a tweet, stating, > "10 trillion tokens processed daily. 10,000+ customers. 40x faster inference than some alternatives. That’s @FireworksAI_HQ and today, we’re co-leading their $250M Series C funding." This highlights the company's significant operational scale and technological edge in the rapidly evolving AI landscape. Fireworks AI currently serves over 10,000 customers, including major enterprises like Uber, Shopify, and Genspark.

Founded by a team previously instrumental in building PyTorch at Meta, Fireworks AI aims to democratize AI by providing developers with tools to scale and build faster. Co-founder and CEO Lin Qiao emphasized the company's mission: "Our mission is to enable every business to achieve automated product and model co-design to reach maximum quality, speed, and cost-efficiency using generative AI." The platform specializes in enabling enterprises to own and customize their AI solutions, avoiding vendor lock-in.

Fireworks AI offers an inference and infrastructure platform that provides access to hundreds of state-of-the-art open-source models across various modalities, alongside advanced fine-tuning options. Their technology delivers up to 40 times faster inference performance and an 8 times reduction in cost compared to some alternatives, by optimizing how models use computing resources. This efficiency is crucial for companies moving AI applications from prototype to production at scale.

The new capital will be strategically deployed to deepen research into tuning and inference alignment, expand their product into a comprehensive AI creation toolchain, and scale global compute infrastructure. This includes increasing their computation footprint by three to four times over the next year, while continuously working to minimize cost per token and maximize system utilization. The company's focus remains on empowering developers to build, deploy, and scale AI on their own terms.