Deploy into your own Google Cloud project, on the A3 and A2 GPU VMs you already hold, inside your VPC. Your data, models, and inference stay in your project and your network. Saturn Cloud adds the platform layer: managed fine-tuning, inference endpoints, per-token metering, and multi-tenant governance.
Why Google Cloud + Saturn Cloud
Google Cloud gives you the compute, storage, and networking. Saturn Cloud gives your teams a managed AI development and serving platform on top of it, instead of months spent assembling one internally.
Saturn Cloud installs into your Google Cloud project on GKE, using Cloud IAM, your VPC, and your firewall rules. Data stays in your Cloud Storage buckets and your network. You keep your committed use discounts and reservations.
Fine-tune open models (full-weight or LoRA), deploy to OpenAI-compatible inference endpoints, and meter usage per token. Managed environments, distributed training, scheduled jobs, and experiment tracking, all from one interface.
Run on A3 (H100 and H200), A2 (A100), and G2 (L4) VMs. Saturn Cloud sets the torchrun and DeepSpeed environment variables, coordinates multi-node jobs across GPUDirect, and reclaims idle GPUs automatically.
Sign in with Google Cloud IAM. RBAC, shared projects, and cost tracking are included, so access and usage attribution match the identity system you already run.
How it works
GPU VM capacity, GKE, Cloud IAM, VPC, and Cloud Storage. Google Cloud already manages the hardware, drivers, and Kubernetes control plane. You keep full control over networking and security policy.
Deploys onto your GKE cluster inside your project. Engineers self-service their own fine-tuning jobs, inference endpoints, and training runs. No YAML, no cluster administration, no DevOps bottleneck.
Log in, pick a GPU, upload a dataset. Fine-tune a model, deploy it to an inference endpoint, and start serving tokens. Pre-configured with CUDA, drivers, and standard AI frameworks.
The difference
| Building internally on Google Cloud | Saturn Cloud on Google Cloud |
|---|---|
| Months of engineering to assemble fine-tuning pipelines, inference serving, and per-token metering | Production-ready platform deployed in your project in days |
| Custom Cloud IAM integration, access controls, and per-team resource management | Cloud IAM SSO, RBAC, shared projects, and cost tracking included |
| Multi-node training coordinated by hand across GKE and GPUDirect | torchrun and DeepSpeed environment variables set automatically |
| GPU idle time from manual provisioning and no automatic reclamation | Automatic idle detection and shutdown with GPU VMs reclaimed when unused |
| No usage attribution across users and projects | Usage tracking and cost allocation per user and project out of the box |
| Locked to a single environment | Same Saturn Cloud experience on-prem, neocloud, or another hyperscaler |
Saturn Cloud resolved my demand for high-performance cloud GPUs and it significantly saved me time. My performance increased by double compared to my previous experience.
— Sara F, Developer