Quadra Video Server
Video Processing with AI
Built on the Supermicro 1114S-WN10RT server platform, NETINT’s Quadra Video Server boasts ultra-high density encoding capacity enabled by ten T1U VPUs (video processing units).

Codensity G5 2nd Gen chip
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CPU Options | AMD EPYCTM 7232P Server Processor (8-core) AMD EPYC 7543P Server Processor (32-core) AMD EPYC 7713P Server Processor (64-core) |
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Operating System | Ubuntu 20.04.05 LTS (as of May 2023) |
Memory | 8x 16GB DDR4-3200 |
Storage | 400GB M.2 SSD |
NVMe Support | 10x |
PCIe Expansion | Up to 3x PCIe slots |
Network Options | Dual 10GBase-T LAN |
Power Consumption | ~500W |
Power Supply | 700W: 100 – 140Vac 750W: 200 – 240Vac 750W: 200 – 240Vdc (CCC only) |
Transcoders | 10x NETINT Quadra T1U |
Encoding Capacity | Up to 40 4Kp60 or 320 1080p30 |
Codec Support | H.264 – Encode/Decode HEVC – Encode/Decode VP9 – Decode AV1 – Encode |
Transcoder Software | FFmpeg, GStreamer |
Physical Dimensions | W: 17.2” (437mm), H: 1.7” (43mm), D: 23.5” (597mm) |
Rack Size | 1U |
Weight | 39 lbs (17.69 kg) (includes 10 processors) |
Environmental | 50 degrees F to 95 degrees F Operating Temperature, 8% to 90% Operating Relative Humidity |
Power Inputs | 100 – 140Vac / 8 – 6V / 50-60Hz 200 – 240Vac / 4.5 – 3.8A / 50-60Hz 200 – 240Vdc / 4.5 – 3.8A (CCC Only) |
Certifications | RoHS Compliant, UL Approved |
Quadra
Work Flow


This is why Google built a custom chip for YouTube
For everyone else who isn't Google, we did the heavy lifting for you
Google’s ASIC called ‘Argos,’ helps YouTube encode and process videos much more efficiently. Argos chips provide “up to 20-33x improvements in compute efficiency compared to its previous traditional server set up,” according to a Google executive. Another report suggests that Argos replaced over 10 million Intel CPUs in YouTube.
The real cost of live streaming
Cost comparison supporting 100 HD streams, 24/7, across 3 video encoding scenarios, over a three year period.
Companies that converted their software encoding to Smart VPUs realized 75-85% savings in their data center’s OPEX expenses.
