Baseten
Category: AI Infrastructure
A serverless infrastructure platform designed for machine learning engineers to deploy, manage, and scale AI models in production with high performance and minimal operational overhead. Baseten was founded in 2019. The company is led by Tuhin Srivastava. Based in San Francisco, USA. Team size: 101-500. Total funding raised: ~$2.085B total across 7 rounds. Latest round: Series F. Key investors include IVP, CapitalG, NVIDIA, Spark Capital, Greylock, BOND, Conviction, 01A, Altimeter, Battery Ventures, South Park Commons, Lachy Groom.
AMW Analysis
Baseten operates a serverless infrastructure platform that lets machine learning engineers deploy, manage, and scale AI models in production, aiming to remove the operational burden of managing GPU infrastructure through a Python-first, developer-centric environment built for high-throughput inference. Founded in 2019 and based in San Francisco, the company has raised roughly $585 million across six rounds since inception.
Recent news flow centers on a rapid escalation of capital raised and valuation. In January 2026, Baseten closed a $300 million Series E co-led by IVP and CapitalG, including $150 million from Nvidia, which doubled its valuation to $5 billion just six months after its prior raise. By June 2026, reporting indicated Baseten was close to finalizing an additional $1.5 billion round at a $13 billion valuation, arriving only five months after the Series E. Taken together, the sequence of rounds — each larger and priced higher than the last within a short span — points to accelerating investor demand for inference-focused AI infrastructure as a category.
AMW analysis, generated from 2 tracked news signals.
- Founded
- 2019
- Headquarters
- San Francisco, USA
- Team size
- 101-500
- Total funding
- ~$2.085B total across 7 rounds
Value proposition
Eliminates the complexity of managing GPU infrastructure by providing a developer-centric, Python-first environment that reduces model deployment time from weeks to minutes while optimizing for high-throughput inference.
Products and solutions
Truss: An open-source model packaging standard for seamless transition from development to production., Serverless GPU Inference: Scalable infrastructure for running models like Llama 3, Mistral, and Whisper., Baseten Chains: A framework for building and deploying multi-step, complex AI workflows and model pipelines., Model Monitoring & Observability: Integrated tools for tracking model performance, latency, and resource utilization., Custom Runtimes: Support for specialized hardware requirements and optimized execution environments.
Unique value
Baseten bridges the 'deployment gap' by offering an open-source packaging standard (Truss) that ensures models run identically in local environments and on production-grade cloud GPUs.
Target customer
Machine learning engineers, data scientists, AI startups, and enterprise engineering teams moving LLMs and generative AI into production.
Industries served
Technology & Software (SaaS), Healthcare & Life Sciences, Financial Services, E-commerce & Retail, Media & Entertainment
Technology advantage
Proprietary GPU orchestration layer that significantly reduces 'cold start' times for large language models (LLMs) and optimizes autoscaling based on real-time inference demand, offering better cost-performance ratios than generic cloud providers.
How they differentiate
Baseten differentiates through its open-source model packaging standard, Truss, which ensures parity between local development and production environments. It also offers 'Baseten Chains' for complex, multi-model workflows and a highly customizable serverless GPU orchestration layer that minimizes cold starts.
Main competitors
Replicate, Modal, Together AI, Anyscale
Key partnerships
NVIDIA (Strategic investor — $150M in Series E, deep GPU optimization partnership), Cloud Infrastructure Providers (AWS, GCP for underlying compute), Open-source communities (Lead maintainers of Truss), Model Providers (Optimized hosting for Meta's Llama, Mistral AI, DeepSeek, Qwen, GLM models), Parsed (Acquired Dec 2025 — reinforcement learning / post-training optimization), Inferless (Acquihired Mar 2026 — inference infrastructure team)
Notable customers
Abridge, Clay, Cursor, OpenEvidence, Notion, Gamma, Writer, Sourcegraph, Zed Industries, Wispr, ClickUp, Mercor
Major milestones
Launched Truss, an open-source standard for model packaging, Raised $40M Series B to scale global GPU infrastructure in March 2024, Raised $75M Series C in February 2025 at $825M valuation, Raised $150M Series D in September 2025 at $2.15B valuation led by BOND, Acquired Parsed, a reinforcement learning startup, in December 2025, Raised $300M Series E in January 2026 at $5B valuation led by IVP and CapitalG with NVIDIA investment, Acquihired Inferless team in March 2026 for inference infrastructure expertise, Raised $1.5B Series F in June 2026 at $13B valuation led by Altimeter, Conviction, and Spark Capital
Growth metrics
Achieved a $13B valuation in June 2026 (Series F); ~20x revenue growth YoY; 40x inference volume growth over the last year; processes 1B+ inference calls daily across 87 clusters and 18 clouds; nearly 400 employees as of Aug 2026.
Market positioning
Enterprise-grade AI inference infrastructure provider focusing on high-performance deployment of open-source and custom models.
Geographic focus
Global (Cloud-based), with a primary business focus on North America and Europe.
Patents and IP
No specific public patents disclosed; focuses on proprietary orchestration logic and open-source contributions to the ML ecosystem.
About Tuhin Srivastava
Tuhin Srivastava is the Co-founder and CEO of Baseten. He was previously the Co-founder of Shape (a 3D body scanning company), which was acquired by Carbon Health in 2021. His professional background includes serving as an early Software Engineer at Gumroad and an Investment Banking Analyst at Macquarie Group. He holds a BS in Electrical Engineering from the University of Southern California.
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Official website: https://www.baseten.co
