Coming soon: NVIDIA Tesla P40, 24 GB VRAM

FFmpeg GPU Server

Transcode video with FFmpeg and NVIDIA NVENC hardware encoding on an NVIDIA Tesla P40 (24 GB VRAM, Pascal architecture). GPU servers are not orderable yet; contact us to be notified when they are.

$ apt install ffmpeg && ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i input.mp4 -c:v h264_nvenc -preset p7 output.mp4
# Example install command

What is FFmpeg GPU on a GPU VPS?

FFmpeg built with NVIDIA support uses NVENC for encoding and NVDEC for decoding, which is much faster than CPU-only transcoding.

FFmpeg GPU on a VPS.org GPU server

NVENC Encoding

Hardware H.264 and H.265 encoding.

NVDEC Decoding

Hardware video decoding frees the CPU for other work.

4K Pipelines

24 GB of VRAM leaves room for high-resolution video pipelines.

Multiple Streams

Encode several streams in parallel on the GPU.

Popular FFmpeg GPU Use Cases

VOD platform encoding
Live stream transcoding
Social media processing
Security footage conversion
Media archival
Thumbnail generation

Planned GPU Specifications

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5
CUDA Cores3,840
FP3212 TFLOPS
INT847 TOPS
Memory BW346 GB/s
ArchitecturePascal (GP102)
PassthroughPCIe passthrough

Frequently Asked Questions

What is FFmpeg GPU on a GPU VPS?

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FFmpeg GPU can use an NVIDIA GPU to speed up its work. VPS.org GPU servers are not available to order yet; contact us to hear when they are. FFmpeg GPU is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for FFmpeg GPU.

How do I set up FFmpeg GPU on a GPU VPS?

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GPU servers are not available to order yet. Today you can run FFmpeg GPU on a regular CPU plan, where it works far more slowly than on a GPU: SSH in and run apt install ffmpeg && ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i input.mp4 -c:v h264_nvenc -preset p7 output.mp4.

How much VRAM do I need for FFmpeg GPU?

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VRAM needs for FFmpeg GPU depend on the model and batch size; check the project documentation for current figures.

How much would a GPU server for FFmpeg GPU cost?

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GPU pricing will be published when GPU servers can be ordered. Contact us if you want to hear when that happens.

Can I run other tools alongside FFmpeg GPU?

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Yes. Every VPS.org server comes with full root access, so you can run other tools alongside FFmpeg GPU within the server's RAM and storage.

Do I get full root on the FFmpeg GPU GPU VPS?

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Every VPS.org server comes with full root SSH access, so you can install drivers, libraries and FFmpeg GPU however you need.

Does VPS.org preinstall CUDA for FFmpeg GPU?

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No. No server comes with a CUDA runtime or NVIDIA driver preinstalled, and GPU servers are not available to order yet. You install the versions FFmpeg GPU needs yourself.

Does my FFmpeg GPU GPU VPS persist between sessions?

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Yes. VPS.org servers are persistent virtual machines, not ephemeral instances: FFmpeg GPU models, configs and data stay on the server's SSD storage until you delete them.

Where should I store data for my FFmpeg GPU workload?

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Keep working data on the server's SSD for fast access during FFmpeg GPU runs, and copy finished artifacts (weights, generations, embeddings) to storage outside VPS.org; snapshots and backups stay on the same storage cluster.

Can I scale my FFmpeg GPU GPU VPS later?

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You can upgrade any VPS.org server to a larger plan from the control panel; the resize restarts it and your FFmpeg GPU install carries over. GPU servers are not available yet.

Are backups available for my GPU VPS?

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Yes. Backups are a paid add-on (daily +30% of the plan price, kept 7 days; weekly +20%, kept 28 days) and snapshots are free, which is useful before long FFmpeg GPU runs. Both stay on the same storage cluster as the server.

Can I get a refund?

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Contact support within 30 days of your first purchase to request a refund. GPU servers are not sold yet, so no GPU order is involved.

Want to Run FFmpeg GPU on a GPU Server?

GPU servers are not orderable yet. Tell us about your workload and we will let you know when they are.