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GPU Infrastructure for Game Studios

On-demand GPU compute for rendering, AI research, automated testing, and creative pipelines — at a fraction of hyperscaler pricing, with no idle hardware costs.

My Instances+ New Instance
Lightmap-BakeRunning
Container·a7f3c1e2
NVIDIA4 x RTX 5090 (32GB)
64 CPU | 256GB RAM
NPC-Dialogue-R&DRunning
Container·b2d8e4f9
NVIDIA1 x L40S (48GB)
30 CPU | 120GB RAM
CI-GPU-RunnerRunning
Container·c9a1b7d3
NVIDIA1 x RTX PRO 6000 (48GB)
30 CPU | 120GB RAM
Asset-Gen-PipelineSetting up
VirtualMachine·e94237d4
NVIDIA1 x H100 (80GB)
64 CPU | 512GB RAM

For Game Studios

Serious GPU Compute Without the Overhead

CloudRift is not a managed game server service. It's a GPU infrastructure layer — programmable access to GPU containers, VMs, and bare metal with the billing and monitoring to run it operationally. For studios, that means serious compute without procurement cycles, idle hardware, or hyperscaler lock-in.

  • Persistent storage across sessions
  • VMs, containers, or bare metal
  • Full API and CI/CD integration
  • Pre-configured AI environments

Overview

Three Ways Studios Use CloudRift

Production Pipeline Support

Replace idle render farms with on-demand burst capacity. Containerize your bake or render pipeline, dispatch to multi-GPU clusters, and pay only for the hours you use — not the months between crunch cycles.

RenderingAutomated QA & PlaytestingCI/CD Test WorkloadsMultiplayer & Server HostingAI-Assisted Asset Creation

AI Research for Game Studios

Self-serve GPU access for AI researchers and ML engineers — no queue, no quota request, no IT ticket. Fine-tune models on your game's lore, prototype playtesting bots, and run experiments with persistent storage across sessions.

Jupyter & VS Code EnvironmentsNPC & Dialogue ResearchCustom Docker-Based AI PipelinesAI Tool Prototyping

Broader Platform Use

Unified GPU layer across production, R&D, and DevOps with per-team cost attribution. On-demand capacity eliminates render farm CapEx. White-label deployment lets publishers run branded GPU platforms across all their studios.

Shared GPU Layer for Production & R&DBackend AI FeaturesWhite-Label GPU & Inference ManagementCross-Studio Compute Sharing

Use Cases

What Studios Run on CloudRift

Concrete GPU workflows that studios deploy today.

Rendering & Lightmap Baking

Package Unreal's headless -buildlighting, Blender, or Movie Render Queue into containers and dispatch to multi-GPU instances. A 6-hour bake parallelized across a GPU cluster finishes in under an hour — no render farm sitting idle between cycles.

3D rendering pipeline

Automated QA & GPU CI/CD

Provision GPU instances as ephemeral CI runners via the API. Visual regression, rendering correctness, and performance profiling — per-PR, not nightly.

NPC Dialogue & AI Research

Fine-tune open-weight models on your game's lore. Serve via OpenAI-compatible API. Integrate into your engine prototype in the same sprint.

Creative Pipelines

Run ComfyUI, Invoke, Stable Diffusion, or custom pipelines on cloud GPUs. Full IP control over generated assets — no third-party ToS concerns.

ComfyUI node graph workflow

The CloudRift Advantage

On-Demand GPU Power

Spin up instances in seconds — no procurement, no quota requests.

Pay-As-You-Go

No CapEx, no idle hardware. Billing stops when instances stop.

No Ecosystem Tax

No egress fees, no IAM overhead, no forced service bundling.

Persistent Storage

Render outputs, checkpoints, and assets survive across sessions.

Faster Iteration

Parallelize renders and experiments. Ship more per sprint.

No Vendor Lock-in

Open stack, NVIDIA + AMD. Workloads stay portable.

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FAQ

Frequently Asked Questions

RTX 4090, RTX 5090, RTX PRO 6000, H100, H200, and AMD MI350X — available on-demand or reserved. Choose VMs, containers, or bare metal depending on your workload. No minimum commitment required.
CloudRift is purpose-built for GPU compute. On-demand rates are typically 2-3x lower than hyperscaler equivalents. No egress fees, no forced service bundling, no quota approval process. Instances spin up in seconds. That said, hyperscalers win on managed services, global reach, and enterprise SLAs — a mature studio uses both.
CloudRift is optimized for dev/test server hosting, not production matchmaking at scale. No managed matchmaking, session management, or DDoS tooling. For QA environments, load testing, and internal playtesting it works well. For player-facing live services, purpose-built solutions like GameLift are more appropriate.
Yes. CloudRift is infrastructure, not a managed service. If your pipeline is "open the editor, click the button," there's a porting cost before you see benefit — budget 2-4 weeks of Tools Programmer time to containerize key workflows. Studios with existing DevOps or build engineering functions will see value fastest.
Yes. Package Unreal's headless -buildlighting, Blender, or Movie Render Queue into Docker containers, push to CloudRift, and run on multi-GPU instances. Persistent storage keeps assets hot between jobs without re-uploading each frame.
Volumes persist independently of instance lifecycle — backed by enterprise storage (Ceph, DDN, WEKA). Attach to any instance, detach when done, reattach later. Models, checkpoints, project files, and render assets survive across sessions.
Yes. Researchers provision GPU instances with Jupyter Lab or VS Code in minutes — no IT tickets. Team management lets you set per-user budgets and track spending. Custom Docker images with your PyTorch environment just run.
Yes. CloudRift supports white-label deployment with multi-tenant management, per-studio cost attribution, and custom branding. Studios onboard as tenants with compute quotas while a central tech team manages capacity planning.
Latency guarantees at production game scale are not CloudRift's focus. For turn-based or background AI tasks the latency is fine, but for sub-50ms player-facing inference, purpose-built inference services are a better fit. CloudRift is strongest for research, prototyping, and backend AI workloads.
Get in touch

Ready to Talk GPU Infrastructure?

Whether you're exploring render farm alternatives, AI research environments, or a unified GPU platform for your studios — we'd like to understand your setup.