--- title: "Run Unreal Pixel Streaming on a cloud GPU from $0.080/hr | PowerGPU" description: "Unreal Pixel Streaming on a fixed-price cloud GPU: one-click template, running in ~30 s, from $0.080/hr on RTX A5000. Best GPUs, volumes, per-second billing." url: https://powergpu.ai/templates/unreal-pixel-streaming last_modified: 2026-09-14T11:04:20+00:00 prices_as_of: 2026-09-14 site: PowerGPU (powergpu.ai) --- Template · Specialised · CUDA 12.8 # Run Unreal Pixel Streaming on a cloud GPU, in 30 seconds Stream an Unreal Engine app to the browser — pixel streaming on a cloud GPU. Stream a packaged Unreal Engine application to any browser: the template runs the signalling server and your Linux build with hardware encode on the GPU. Demos, configurators and virtual showrooms scale by adding instances, not by shipping installers. From **$0.080** /hr on an interruptible RTX A5000. Unreal Pixel Streaming powergpu/unreal-pixel-streaming (CUDA 12.8) (SSH) (Jupyter) Pinned image, rebuilt on upstream releases. Override env, ports and disk at deploy. ### Running in ~30 s Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this. ### Template is free You pay the GPU price only: Unreal Pixel Streaming on a RTX 4090 is $0.327/hr on-demand, $0.163/hr interruptible, billed per second. ### Volumes for state Models, datasets and outputs live on a $0.08/GB/mo volume; the instance stays disposable. ### Private by default Dedicated GPU, encrypted disk, crypto payments, no KYC, no stored IPs — Jupyter and SSH behind your own credentials. ## Best GPUs for Unreal Pixel Streaming Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks. | Tier | GPU | VRAM | On-demand | Interruptible | Why this card | | | --- | --- | --- | --- | --- | --- | --- | | (Good) | [RTX 4090](https://powergpu.ai/gpu/rtx-4090) | 24 GB | $0.327 | $0.163 | High frame rates with a strong NVENC at consumer prices. | [Deploy](https://cloud.powergpu.ai/?gpu=rtx-4090) | | (Better) | [RTX A5000](https://powergpu.ai/gpu/rtx-a5000) | 24 GB | $0.161 | $0.080 | Blower-cooled workstation card for long-running streams. | [Deploy](https://cloud.powergpu.ai/?gpu=rtx-a5000) | | (Best) | [L40S](https://powergpu.ai/gpu/l40s) | 48 GB | $0.514 | $0.257 | Datacenter Ada with dual encoders for many concurrent viewers. | [Deploy](https://cloud.powergpu.ai/?gpu=l40s) | Need more VRAM? The [full catalogue](https://powergpu.ai/gpus) lists all 80 models with live availability; the [VRAM guide](https://powergpu.ai/guides/llm-vram-requirements) sizes models to cards. ## Deploy Unreal Pixel Streaming from the console, CLI or API Pick the template in the [console](https://cloud.powergpu.ai/) deploy bar, or script it: - **Console** — filter by GPU, choose *Unreal Pixel Streaming* in the template picker, set disk and env, deploy. - **CLI** — pip install powergpu, then the command on the right. [CLI reference](https://powergpu.ai/cli). - **API** — POST /v1/instances with "template": "unreal-pixel-streaming". [REST reference](https://powergpu.ai/api). - **Own image** — any OCI reference works too; we inject the NVIDIA runtime. [Template docs](https://powergpu.ai/docs/templates). *deploy — unreal-pixel-streaming* ``` $ powergpu launch --gpu rtx-4090 --template unreal-pixel-streaming \ --disk 100 --volume models:/workspace/models ✓ instance i-7a41c0e2 running (27.9s) # Unreal Pixel Streaming · RTX 4090 · $0.327/hr · per second # https://i-7a41c0e2.powergpu.ai:8888 (TLS) $ powergpu stop i-7a41c0e2 # billing ends this second ``` ## What is inside the Unreal Pixel Streaming template - **Image**: powergpu/unreal-pixel-streaming - **CUDA**: CUDA 12.8 - **Access**: SSH shell · JupyterLab on a mapped port - **Category**: [Specialised](https://powergpu.ai/templates#tools) - **Storage**: Instance NVMe disk (sized at deploy) + optional [network volumes](https://powergpu.ai/products/volumes) - **Billing**: GPU price only, per second — no template fee, no setup fee ## Other specialised templates - [Hashcat CUDA on a cloud GPU](https://powergpu.ai/templates/hashcat-cuda) — GPU password recovery for authorised security testing — CUDA-accelerated Hashcat. - [All 37 templates](https://powergpu.ai/templates) ## Unreal Pixel Streaming on a cloud GPU: FAQ Environment variables, ports and custom images are covered in the [template docs](https://powergpu.ai/docs/templates). **How much does it cost to run Unreal Pixel Streaming on a cloud GPU?** Only the GPU price — the template is free. From $0.080/hr on an interruptible RTX A5000, $0.327/hr on-demand on a RTX 4090. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month. **How long does Unreal Pixel Streaming take to start?** About 30 seconds from the deploy click: the image is pre-cached on hosts, ports are mapped and TLS is terminated for you. Restarting a stopped instance is faster, and your disk is exactly as you left it. **Can I keep my models and outputs between sessions?** Yes — attach a volume at deploy. Everything on the volume survives instance destruction and mounts on the next instance in the region in seconds, at $0.08/GB/month. The instance disk itself survives stop/start but not destroy. **How many viewers per GPU?** One interactive session per GPU for a full 3D scene is the safe assumption; lighter scenes can share a card. Scale horizontally by launching more instances behind your matchmaker. --- *About PowerGPU:* PowerGPU (powergpu.ai) is a cloud GPU rental service offering 80 NVIDIA GPU models — from the RTX A2000 at $0.024/hr to the B300 — at fixed prices set at least 30% below the public GPU marketplace median and re-checked weekly (H100 SXM: $1.428/hr on-demand). Billing is per second with no minimums; payment is crypto only (USDT, BTC, XMR, ETH, SOL, LTC, TRX) with no KYC. Instances run in Tier-III datacenters across 32 regions with a 99.9% uptime SLA and deploy in about 30 seconds from the web console (cloud.powergpu.ai) or the REST API. Source: https://powergpu.ai/templates/unreal-pixel-streaming · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt