Private GPUs
in < 3 Seconds
Pay Per Second.
Secure GPU workloads. Your API keys, your container. 70+ models ready to deploy.
Custom Docker orchestration with secure API key provisioning. Only you can access your GPU. From A100s to B300s. Per-second billing means you only pay for what you use.
Chat with Compute3.AI
Why Compute
The fastest, most flexible GPU infrastructure for AI workloads
Lightning Fast
Boot any GPU workload in under 3 seconds. Custom Docker orchestration means zero cold starts, zero wait times.
- Sub-3 second boot times
- Instant container deployment
- Pre-warmed GPU instances
Pay Per Second
No hourly minimums. No monthly commitments. Pay only for the exact seconds you use. Spin up, use, tear down.
- Per-second billing granularity
- No hourly minimums
- No contracts or commitments
Secure & Private
Your API keys provisioned directly to your container. No shared access. You're the only one with access to your GPU.
- Isolated container environments
- Secure API key provisioning
- Private GPU access only
GPU Workloads in < 3 Seconds
Deploy any AI workload with secure, per-second billing. Your API keys, your GPU.
LLM Inference Servers
Deploy production-ready LLM servers in under 3 seconds. Run any model with vLLM, SGLang, Ollama, or TGI.
- vLLM for maximum throughput
- SGLang for structured generation
- Ollama & TGI support
- Any model from HuggingFace
Media Generation
ComfyUI, Automatic1111, and Fooocus ready to go. Images with Flux & HiDream, video with Wan 2.2, audio with Whisper & 50+ more models.
- ComfyUI node-based workflows
- Image: Flux, HiDream, Qwen
- Video: Wan 2.2, Hunyan
- Audio: Whisper, CSM + many more
Development Environments
GPU-accelerated JupyterLab, VSCode Server, or bring your own Docker container. Perfect for research and experimentation.
- JupyterLab with GPU support
- VSCode Server with CUDA
- Custom Docker containers
- PyTorch environments ready to go
Training & Fine-tuning
Fine-tune models with Axolotl, LLaMA Factory, Unsloth, or DeepSpeed. Faster training, lower costs.
- Axolotl for easy fine-tuning
- LLaMA Factory WebUI
- Unsloth for 2x faster training
- DeepSpeed for distributed training
World-Class GPU Fleet
From cost-effective L4s to cutting-edge B300s. Choose the right GPU for your workload.
Distributed Training at Scale
Train on 8x to 512x GPU clusters. Scale from fine-tuning to foundation model training.
Small-scale fine-tuning
Medium-scale training
Large-scale training
Massive distributed training
Up to 512x B200 Clusters
Need massive compute for foundation model training? We can provision up to 512 B200 GPUs with high-speed interconnects.
Custom configurations available
High-Speed Interconnects
InfiniBand & NVLink for maximum throughput
Flexible Frameworks
DeepSpeed, PyTorch FSDP, Megatron-LM
Checkpointing & Monitoring
Built-in fault tolerance and observability
One Command. <3 Seconds.
Deploy any workload with our CLI. From inference to training, boots in under 3 seconds.
# Deploy vLLM with Llama 3 70B on H100
c3 deploy vllm \
--model meta-llama/Llama-3-70b \
--gpu h100
# Launch ComfyUI on A100
c3 deploy comfyui \
--gpu a100-80gb
# Start JupyterLab with CUDA
c3 deploy jupyter \
--gpu a100-40gb \
--image pytorch/pytorch:latest
# Deploy Ollama with custom models
c3 deploy ollama \
--gpu l40s \
--models llama3,mistral
# Fine-tune with Axolotl on 8x H100
c3 train axolotl \
--config fine-tune.yml \
--gpus 8 \
--gpu-type h100GPUs Connected
Uptime SLA
GPU Workloads Launched
Deploy your first model in 60 seconds
No credit card required. Our free tier is perfect for getting started with open-source AI.
