Lambda targets $4 billion funding round ahead of planned IPO

Lambda targets $4 billion funding round ahead of planned IPO
Lambda eyes $4B funding

Cloud-computing provider Lambda is pursuing what could be its last private capital raise before seeking a stock market listing. The round values the Nvidia-backed company at $14.5 billion before new money and points to growing investor interest in AI infrastructure demand.

Highlights

  • Lambda is raising up to $4 billion in a funding round led by Blackstone and Coatue Management, according to people familiar with the matter.
  • The company aims to go public in 2027, depending on execution and market conditions, as stated in a letter to limited partners.
  • Lambda's order backlog jumped to $50 billion in September from $15 billion in June, signaling surging AI infrastructure demand.

Funding plan and IPO timeline

As reported by Reuters, citing The Wall Street Journal, Lambda is raising up to $4 billion in a funding round led by Blackstone and Coatue Management, citing people familiar with the matter.

The company is aiming to go public in 2027, depending on execution and market conditions, according to a letter to its limited partners reviewed by the Journal.

Order backlog signals AI infrastructure demand

Lambda's backlog of unfilled orders grew to $50 billion in September from $15 billion in June, according to the letter reviewed by the Journal.

The increase suggests strong demand for cloud and computing capacity tied to artificial intelligence workloads as investors assess the company's growth prospects ahead of a planned IPO. Lambda did not immediately respond to a Reuters request for comment.

In our earlier article, we reported on how funding for AI infrastructure is moving into the asset-backed securities market via equipment loans and leases that include GPU-linked collateral. We noted that Stonebriar’s ABS sale—along with similar deal references—signaled broader investor acceptance of securitized equipment finance as another channel to fund the hardware needed for AI workloads.

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