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NETINT Technologies

Encoding & SoftwareLive StreamingCloud Video

Website

www.netint.com

Contact

info@netint.com

Category

Encoding & Software

Type

Vendor

Blog / NewsLinkedIn
Updated Aug 24, 2026 ·

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NETINT Technologies

NETINT Technologies homepage screenshot

Overview

NETINT Technologies is the creator of the VPU (video processing unit) category, offering ASIC-based video encoding solutions that dramatically reduce energy consumption and operational costs by 20-40x compared to CPU-based encoding. The company's hardware supports advanced codecs including AV1, 8K, and HDR, and includes on-chip AI engines for image processing. NETINT has been recognized with a Technology & Engineering Emmy® Award for its efficient hardware video accelerators, and has partnered with Akamai to deploy VPU-powered video encoding in the cloud, demonstrating its credibility in hyperscale media processing.

Products & Services

Quadra T1M VPU

Purpose-built silicon the open market deploys to encode video at scale economically.

Quadra T1U VPU

Purpose-built silicon the open market deploys to encode video at scale economically.

Quadra T1A VPU

Purpose-built silicon the open market deploys to encode video at scale economically.

Quadra T2A VPU

Purpose-built silicon the open market deploys to encode video at scale economically.

Quadra Video Server

The hardware platform built to maximize video encoding.

Quadra Mini Server

The hardware platform built to maximize video encoding.

Bitstreams

The control plane to convert VPU silicon into a manageable platform.

Leadership

  • Joshua Zhu

    CEO

  • Mark Donnigan

    Chief Marketing Officer

  • Randal Horne

    Chief Revenue Officer (CRO)

NETINT Technologies in the News

  • Aug 24, 2026
    Encoding
    Zixi and NETINT integration offloads live transcoding to purpose-built VPUs

    Zixi and NETINT have published a technical overview detailing the integration of Zixi's software-based transport and control plane with NETINT's hardware-based video processing units. The collaboration aims to improve live streaming workflow reliability and transcoding density by offloading processing tasks from general-purpose CPUs to purpose-built hardware.

  • Aug 19, 2026
    Encoding
    NETINT Quadra VPU integration brings hardware encoding to i3D.net infrastructure

    NETINT and i3D.net have announced a partnership to integrate NETINT's Quadra video processing units (VPUs) into i3D.net's managed bare metal and private cloud infrastructure. The collaboration aims to provide dedicated hardware-based encoding for latency-sensitive workloads such as cloud gaming and interactive streaming.

  • Jul 28, 2026
    Encoding
    NETINT details seven-step technical framework for VPU migration and infrastructure

    NETINT Technologies has released a seven-step technical framework for migrating streaming video workloads from CPU-based processing to their Quadra Video Processing Units (VPUs). The guide provides engineering teams with recommended strategies for validating hardware, ensuring service equivalence through feature parity, and establishing reliable rollback paths during the transition.

  • Jul 24, 2026
    Encoding
    NETINT Quadra VPU benchmarks reveal 7x throughput gain over CPUs

    NETINT Technologies explains the operational advantages of using dedicated video processing units (VPUs) over general-purpose CPUs for video encoding pipelines. The technical breakdown details how keeping decode, scaling, and encode stages on a single hardware device reduces data bus contention and increases aggregate throughput for multi-session streaming workflows.

  • Jul 20, 2026
    Encoding
    VPU shift over software: Priority for encoding moves to hardware architecture

    NETINT provides a technical argument for prioritizing silicon architectural selection over software-based encoder choice for video processing workflows. The analysis advocates for a heterogeneous compute model where purpose-built VPUs handle intensive video encoding to improve density and power efficiency relative to traditional CPU-based implementations.

  • Jul 16, 2026
    Encoding
    NETINT advocates VPUs over CPUs to solve high-density encoding constraints

    NETINT CMO Mark Donnigan argues that media companies should prioritize video processing units (VPUs) over general-purpose CPUs for large-scale encoding workloads to improve density and power efficiency. The article highlights the company's Quadra T1U hardware as a solution for achieving higher streams per server in modern data centers.

  • Jul 7, 2026
    Encoding
    AV1 adoption to hit 57% as AI moves into core encoding pipelines

    This report from NETINT surveys video encoding professionals on current and future trends including the adoption of AV1, the shift toward hybrid infrastructure, and growing integration of machine learning. The data highlights a transition away from GPU-only hardware and emphasizes that budget and capacity constraints remain the primary barriers to adoption for most organizations.

  • Jul 3, 2026
    Encoding
    NETINT Quadra VPUs target CPU inefficiencies with high-density AV1 encoding

    NETINT Technologies introduced its Quadra VPU product family, utilizing the company's Codensity G5 ASICs for hardware-based AV1, HEVC, and H.264 encoding. The product line is designed to replace CPU-based transcoding in data center, edge, and cloud gaming environments to increase stream density and reduce power consumption.

  • Jun 29, 2026
    Encoding
    NETINT benchmarks claim VPUs deliver 5.8x better efficiency for AV1

    NETINT published a technical blog post arguing that AV1 adoption at scale requires moving encoding workloads from CPUs to purpose-built video silicon. The post cites Quadra VPU benchmarks and quality tests claiming lower watts per stream and bitrate savings versus CPU/GPU-based approaches, including AV1 savings at 1080p and higher density at rack scale.

  • Jun 25, 2026
    Encoding
    NETINT VPUs turn retired servers into 320-stream encoders

    NETINT advocates recommissioning decommissioned servers with its Video Processing Units (VPUs) to expand video encoding capacity. The approach offloads H.264, HEVC, and AV1 encoding to low-power VPUs, achieving up to 32 1080p30 streams per card. This method targets organizations facing GPU/server supply chain delays and seeks to free new servers for AI workloads.

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