GPU power, without
the infrastructure.
Spark GPU gives developers, researchers, and AI builders instant access to high-performance GPU compute — without managing cloud infrastructure. Built on Modal. Ready in minutes.
import sparkgpu # Define your job job = sparkgpu.Job( model="llama3-70b", gpu="H100", prompt="Summarize this document..." ) # Run it — results back in seconds result = job.run() print(result.output)
The Best Model
YOU.GPT Custom AI language models, trained on your data.
What's the most powerful AI model — ChatGPT? Claude? Neither. The best model is the one trained specifically on your interests, your business procedures, and your data. Generic models know everything about the world and nothing about you. Yours does.
With Spark GPU, training your own model isn't a research project anymore. It's an afternoon.
Start Training →Trained on your data · Fine-tuned on your use case · Hosted on your terms
The Problem
Getting GPU compute
shouldn't be a project.
Cloud GPU platforms are powerful — but they're built for infrastructure engineers, not the people who actually need to run things.
- → Setting up containers and environments
- → Managing cold starts and timeouts
- → Figuring out which GPU to use and why
- → Writing boilerplate just to run a job
That's time you're not spending on the work that matters.
Before
- ✗ Write Dockerfile
- ✗ Configure IAM policies
- ✗ Manage cold starts
- ✗ Debug cluster configs
- ✗ Monitor idle costs
After Spark GPU
- ✓ Write your code
- ✓ Submit the job
- ✓ Get results
That's it.
How It Works
Submit a job. Get results.
That's it.
Define your task
Upload your code, data, or model. No Docker required.
Choose your compute
Pick from H100s, A100s, or T4s. We handle the rest.
Run and receive output
Your job runs on dedicated GPUs. Results come back fast.
No YAML. No Kubernetes. No IAM policies.
Just the work you actually need to do.
Built For
Whatever you're running,
we've got the compute.
AI App Builders
Ship AI features fast
Running LLM inference, image generation, or audio processing in your app? Stop managing GPU servers. Deploy a scalable endpoint in minutes.
ML Researchers
Fine-tune without the wait
Fine-tune open-source models on real H100s — without submitting tickets or waiting in cluster queues. Your research, on demand.
Batch Processing
Process at scale
Transcription, video encoding, embedding generation, data pipelines — run massive batch jobs across hundreds of GPUs. Pay only for what you use.
Indie Hackers & Startups
Move fast without infra debt
You're building, not babysitting servers. Get GPU access that scales with you, without the DevOps overhead.
Why Spark GPU
Everything you need.
Nothing you don't.
Instant startup
Jobs start in seconds, not minutes.
No boilerplate
Submit jobs without writing container configs or setup scripts.
Premium hardware
H100s, A100s, T4s — you choose the right GPU for the job.
Pay per second
No idle costs. No minimums. You pay only while your job is running.
Built on Modal
Reliable, battle-tested GPU infrastructure under the hood.
Simple API
One endpoint. Works with Python, cURL, or any HTTP client.
Isolated environments
Every run is sandboxed. Your data stays yours.
Job visibility
Real-time status, logs, and output — always visible.
Try It Live
See it work. Right now.
Pick a demo. Hit run. Watch a real GPU job execute in seconds.
Pricing