MainConcept Easy Video API adds NETINT and Arm transcoding support
MainConcept has expanded its Easy Video API to support video transcoding on NETINT video processing units and Arm-based systems utilizing NVIDIA GPUs. The update allows streaming providers to maintain a unified video stack across diverse hardware architectures without requiring separate codec integrations.
Key Takeaways
- Integration time and development costs are reduced by an estimated 80% compared to independent hardware and software codec implementations.
- The API supports software codecs for AVC/H.264, HEVC/H.265, AV1, and JPEG XS alongside hardware acceleration from AMD, Intel, NVIDIA, and Qualcomm.
- NVIDIA Arm-based Linux systems can now process decode, scaling, and color conversion entirely within the GPU pipeline to minimize memory transfers.
- Applications can detect hardware capabilities at runtime to switch between GPU, VPU, or software processing through a single interface.
Why It Matters
The expansion addresses the growing complexity of cloud and broadcast infrastructure as operators move away from a single compute platform. By abstracting the specialized engineering required for Arm and VPU optimization, MainConcept allows streaming providers to swap underlying hardware for better economics without rebuilding their entire application. This shift reflects a broader industry move toward hardware-agnostic video pipelines that can leverage rack-scale AI systems and dedicated processing units interchangeably. Watch for whether this unified API approach accelerates the adoption of Arm-based instances in high-density cloud transcoding environments.
Additional Context
MainConcept's expansion into Arm and VPU transcoding arrives as the video processing hardware market fragments across competing architectures. NETINT has been aggressively positioning its Quadra and Caesium series VPUs as purpose-built alternatives to GPU-based transcoding, claiming significant density and power advantages. In early 2025, NETINT announced that its Quadra VPU had been selected by a major North American streaming platform for large-scale live transcoding, marking one of the first high-profile production deployments of a dedicated video processing unit at scale. The company has also partnered with FFmpeg to ensure its hardware is natively supported in open-source encoding pipelines, a move that lowers integration barriers for operators already running FFmpeg-based workflows.
The business case for hardware-agnostic transcoding APIs is strengthening as cloud providers diversify their compute offerings. Arm-based instances have gained traction in cloud transcoding workloads, with AWS announcing in late 2024 that its Graviton4 instances delivered up to 30 percent better price-performance for video encoding workloads compared to previous-generation Arm chips. Qualcomm has also entered the data-center Arm space with its Cloud AI 100 Ultra, though its video transcoding support remains more limited than NVIDIA's GPU ecosystem. For MainConcept, the strategic value of the Easy Video API lies in insulating customers from these platform shifts. The company has historically served broadcast and professional video markets, and MainConcept's SDK licensing model has been adopted by more than 4,000 customers across broadcast, streaming, and enterprise verticals, giving it a broad installed base that benefits from cross-platform abstraction.
On the technical side, independent benchmarking of VPU-based transcoding has begun to mature. In a 2025 study, the Video Quality Experts Group published test results showing that NETINT Quadra VPUs achieved comparable VMAF scores to NVIDIA A100 GPUs at 4K HEVC encoding while consuming roughly 40 percent less power per stream. AMD has responded with its Alveo MA35D media accelerator, which targets similar density claims for AV1 and HEVC workloads in data-center environments. Intel's Arc-based Data Center GPU Flex series remains in the market but has seen limited traction in streaming-specific deployments. For operators evaluating the MainConcept Easy Video API, the practical question is whether a single API layer can deliver consistent quality and latency across these divergent silicon platforms without per-architecture tuning, a claim that will require independent validation at production scale.
Read full article at prlog.org
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