In the news release, Runpod’s 2026 State of AI Report Reveals Massive Shift Toward Qwen, Blackwell and Modular Video Pipelines, issued 12-Mar-2026 by Runpod over PR Newswire, we are advised by the company that changes have been made. The complete, corrected release follows:
Runpod’s 2026 State of AI Report Reveals Massive Shift Toward Qwen, Blackwell and Modular Video Pipelines
, /PRNewswire/ — Runpod, the platform that empowers developers to build and run custom AI systems at scale, today announced its first State of AI Report. Built on anonymized platform traffic and GPU utilization data, the report provides a ground-level view of how AI is being used in production across 183 countries, moving beyond industry hype to reveal the infrastructure patterns defining the current era.
The report highlights a significant shift in the open-source landscape, noting that Alibaba’s Qwen has overtaken Meta’s Llama as the most widely deployed self-hosted Large Language Model (LLM) on the platform. Additionally, the data indicates that the market is prioritizing efficiency and modularity; nearly 70% of image workflows now run through ComfyUI, and video upscaling workloads outpace raw generation by a 2:1 ratio.
“This report isn’t a survey of what people say they’re using; it’s an aggregated record of what is being used to generate revenue – and the patterns we’re seeing are much more nuanced.” said Brennen Smith, CTO at Runpod. “The market is pragmatic, optimizing for performance per dollar and inference latency. As AI transitions from experimental to essential infrastructure in verticals like HealthTech and FinTech, we’re seeing a massive diversification in use cases ranging from protein structure prediction to robotics kinematics to real-time coding assistants.”
Key Findings from Runpod’s State of AI Report Include:
- The Rise of Qwen: Qwen has emerged as the dominant open-source LLM, while the ecosystem has been slower to migrate to Llama 4, which currently sees minimal production adoption compared to version 3.x.
- Blackwell Acceleration: Nvidia B200 usage scaled 25x in 2025. Supply for the Blackwell architecture is projected to nearly quadruple by mid-2026.
- Video Strategy: 70% of video generation endpoints incorporate upscaling or enhancement, revealing a “draft then refine” strategy where users run many low-resolution generations before investing compute in final quality.
- Global Developer Ecosystem: While the U.S. leads in user base, India has become the second-largest market, with Europe collectively representing nearly a third of Runpod’s global traffic.
- Standardization of Tooling: vLLM has become the de facto standard for LLM serving, powering 40% of all LLM endpoints on the platform.
Find the full 2026 State of AI Report, including detailed GPU pricing trends and adoption forecasts, here.
Read the blog: The AI market looks nothing like the narrative
About Runpod
Runpod is a globally distributed AI cloud platform that empowers developers at any organization to deploy custom full-stack AI applications – simply, globally, and at scale. With Runpod’s key offerings – Pods, Clusters, Endpoints, and Serverless – developers can develop, train and scale AI applications in one cloud within seconds. Runpod is making cloud computing accessible and affordable without compromising control, customization or cost-efficiency. To learn more, visit https://www.runpod.io/.
SOURCE Runpod
