Funding Round
<cite index="8-6">Fireworks AI, the platform for specialized intelligence enabling companies like Uber and Shopify to train and serve custom models, announced a $1.505 billion Series D round at a $17.5 billion valuation.</cite> <cite index="8-7">The round was led by Atreides Management, Index Ventures, and TCV, with participation from existing investors Evantic, Lightspeed Venture Partners, and NVIDIA.</cite> <cite index="2-4">Bessemer Venture Partners, Menlo Ventures, Insight Partners, Ontario Teachers' Pension Plan, and Lone Pine Capital also participated.</cite>
<cite index="4-9">The Series D replaced earlier discussions of a potential round at a $15 billion valuation and came nine months after Fireworks' $250 million Series C in October 2025 at a $4 billion post-money valuation.</cite> <cite index="4-13">Including the Series D, Fireworks has raised more than $1.8 billion in total funding.</cite>
Company Background
<cite index="2-8">Fireworks was founded in 2022 by CEO Lin Qiao and six co-founders, all former Meta engineers.</cite> <cite index="19-2">Prior to founding Fireworks, Lin Qiao led Meta's PyTorch framework team.</cite> <cite index="20-2">The platform is built on proprietary optimization technologies including the FireAttention custom CUDA (Compute Unified Device Architecture) kernel, speculative decoding pipelines, and the FireOptimizer adaptive serving engine.</cite>
<cite index="15-8">Fireworks operates a usage-based business-to-business inference platform — customers pay per token and per Graphics Processing Unit (GPU)-hour to run hundreds of open-source and fine-tuned models across text, image, audio, and multimodal formats.</cite> <cite index="15-9">Beyond raw inference, Fireworks monetizes fine-tuning, reinforcement learning tooling, and model evaluation — layers that increase switching cost once a customer builds a production pipeline on top of the platform.</cite>
Revenue and Usage Milestones
<cite index="8-8,8-9">The funding comes as Fireworks surpasses $1 billion in annualized revenue run rate, up 5x year-over-year, and nearly tripled the daily volume of tokens served on its platform, from 15 trillion to more than 40 trillion.</cite>
<cite index="3-3">According to the company, more than 95% of those tokens come from models specialized on customers' proprietary data and optimized for specific tasks</cite> — a figure the company cites as evidence of enterprise adoption of customized Large Language Models (LLMs) over commodity frontier alternatives.
<cite index="11-7">The company's gross margin sits at approximately 50%, below the 70%-plus typical of subscription software businesses, due to the GPU infrastructure costs embedded in its cost of goods sold.</cite> <cite index="4-1">Fireworks has told investors it is targeting 60% gross margins through continued GPU optimization and improved utilization efficiency.</cite>
Customers and Competitive Position
<cite index="2-10,2-11">Customers include Uber, Shopify, Doximity, Elastic, GitLab, and MongoDB; legal AI company Harvey and coding tool Cursor have also built on the platform.</cite> <cite index="4-3">The customer base grew from roughly 1,000 companies at the time of the Series B to more than 10,000 companies by October 2025.</cite>
<cite index="2-13">In March 2026, Fireworks announced a partnership with Microsoft that allows Microsoft customers to access models through Fireworks' platform, which draws on computing capacity from more than 20 suppliers.</cite>
<cite index="6-6">Fireworks competes with Together AI and Baseten in the AI inference cloud market.</cite> <cite index="15-3">Together AI raised an $800 million Series C on July 1, 2026 at an $8.3 billion valuation.</cite>
Use of Proceeds and Headcount
<cite index="5-2">New funding will expand compute capacity, engineering teams, and cloud partnerships.</cite> <cite index="2-9">The company's workforce stands at roughly 200, and CEO Lin Qiao has said she plans to triple that figure before the year is out.</cite>
<cite index="8-10">The company's growth reflects how AI strategies are maturing as companies increasingly complement frontier closed models with open models customized for their own data, workflows, and use cases.</cite>