What 1.2 million developers taught me about AI this year

Runpod’s second State of AI Compute report analyzes observed deployment choices across 1.2 million accounts in 186 countries, arguing that usage data offers a clearer view of AI adoption than surveys of intended activity. Agent-initiated deployments grew rapidly to 8.4% of users and 24% of revenue, with longer-running workloads and higher revenue per user, while AI video activity was found to focus largely on post-production such as upscaling rather than generating new footage. The report indicates that teams commonly combine frontier-model APIs with open-weight models, using fine-tuned specialist models for business-specific tasks, and that self-hosted users often adopt newly released open models within weeks, contributing to Qwen’s increased share and Llama’s decline. Resource constraints have also encouraged lower-precision, quantized model deployments, particularly for models larger than 70 billion parameters. Although AI companies remain Runpod’s largest customer segment by revenue, adoption is expanding into sectors including government, fintech, and manufacturing, with Asia identified as the fastest-growing region. Runpod also reviewed its prior GPU supply forecasts, finding that H100 growth was close to expectations, H200 growth lagged, and the broader Blackwell fleet grew faster than expected after newer hardware arrived.

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