Why Lack of Hardware Encoding Delayed VP9 Adoption

This article explores how the early adoption of the VP9 video codec—specifically through the software-based libvpx-vp9 encoder—was severely hindered by a historical lack of dedicated hardware encoding support. While VP9 offered superior compression efficiency over H.264, the high CPU overhead required for software-based encoding delayed its widespread integration across streaming platforms, device manufacturers, and real-time communication software.

The Computational Barrier of Software Encoding

VP9, developed by Google as an open-source and royalty-free codec, was designed to compete directly with HEVC (H.265). It achieved remarkable bandwidth savings, but this compression efficiency came at the cost of immense computational complexity.

In its early years, encoding video into VP9 relied almost entirely on libvpx-vp9, a software encoder that executed on the system’s CPU. Without dedicated Application-Specific Integrated Circuits (ASICs) or GPU-based hardware encoders to offload this work, encoding high-definition or 4K video in real-time was virtually impossible on standard consumer and enterprise hardware. The massive CPU utilization resulted in extremely slow encoding speeds, making it impractical for time-sensitive workflows.

Impact on Streaming Platforms and Infrastructure Costs

For video streaming platforms, the cost of video ingestion and transcoding is a major operational expense. While Google possessed the massive server infrastructure required to transcode YouTube’s vast library into VP9 using CPU power, smaller platforms could not justify the financial and computational expense.

Using libvpx-vp9 meant that servers had to dedicate significantly more CPU cycles per video compared to H.264, which already enjoyed mature, highly optimized hardware acceleration. Because transcoding times were multiplied and server energy costs spiked, most platforms chose to stick with H.264 or wait for HEVC hardware support rather than adopting VP9.

Hurdles in Real-Time Communication and Live Streaming

The lack of hardware encoding was particularly damaging to the adoption of VP9 in real-time communications, such as WebRTC and video conferencing. In a live-streaming or video-calling scenario, encoding must happen instantaneously on the user’s local device.

When devices attempted to use libvpx-vp9 for real-time encoding, the lack of hardware acceleration forced mobile and desktop CPUs to run at maximum capacity. This caused rapid battery drain, severe thermal throttling, and dropped frames. Consequently, developers of video conferencing tools avoided VP9, choosing instead to rely on H.264, which could run coolly and efficiently on any smartphone or laptop chip.

The Hardware Advantage of H.264 and HEVC

While VP9 struggled in the software-only domain, its competitors benefited from a robust hardware ecosystem. Chipmakers like Intel, Nvidia, Qualcomm, and Apple quickly integrated dedicated hardware encoders and decoders for H.264, and later HEVC, directly into their silicon.

This hardware-first approach meant that developers could guarantee smooth, battery-efficient video processing out of the box. Because hardware manufacturers were slow to integrate VP9 encoding pipelines into their chips—partly due to the industry’s initial hesitation around Google’s royalty-free licensing model—VP9 remained a niche choice used primarily by Google-controlled platforms until hardware support finally caught up years later.