Float16.cloud
Overview of Float16.cloud
Float16.cloud: Serverless GPUs for AI Development and Deployment
Float16.cloud is a serverless GPU platform designed to accelerate AI development and deployment. It provides instant access to GPU-powered infrastructure without the need for complex setup or server management. This allows developers to focus on writing code and building AI models, rather than managing hardware.
What is Float16.cloud?
Float16.cloud offers a serverless GPU environment where you can run, train, and scale AI models. It eliminates the overhead of managing infrastructure, Dockerfiles, and launch scripts. Everything is preloaded for AI and Python development, allowing you to get started in seconds.
How does Float16.cloud work?
Float16.cloud provides a containerized environment with native Python execution on H100 GPUs. You can upload your code and launch it directly without building containers or configuring runtimes. The platform handles CUDA drivers, Python environments, and file mounting, allowing you to focus on your code.
Key Features
- Fastest GPU Spin-up: Get compute in under a second, with containers preloaded and ready to run. No cold starts or waiting.
- Zero Setup: No Dockerfiles, launch scripts, or DevOps overhead.
- Spot Mode with Pay-Per-Use: Train, fine-tune, or batch process on affordable spot GPUs with per-second billing.
- Native Python Execution on H100: Run
.pyscripts directly on NVIDIA H100 without building containers. - Full Execution Trace & Logging: Access real-time logs, view job history, and inspect request-level metrics.
- Web & CLI-Integrated File I/O: Upload/download files via CLI or web UI. Supports local files and remote S3 buckets.
- Example-Powered Onboarding: Deploy with confidence using real-world examples.
- Flexible Pricing Modes: Run workloads on-demand or switch to spot pricing.
Use Cases
- Serve Open-Source LLMs: Deploy llama.cpp-compatible models like Qwen, LLaMA, or Gemma with a single CLI command.
- Finetune and Train: Execute training pipelines on ephemeral GPU instances using your existing Python codebase.
- One-Click LLM Deployment: Deploy open-source LLMs directly from Hugging Face in seconds. Get a production-ready HTTPS endpoint with zero setup and cost-effective hourly pricing.
Why choose Float16.cloud?
- True Pay-Per-Use Pricing: Pay only for what you use, with per-second billing on H100 GPUs.
- Production-Ready HTTPS Endpoint: Expose your model as a secure HTTP endpoint immediately.
- Zero Setup Environment: The system handles CUDA drivers, Python environments, and mounting.
- Spot-Optimized Scheduling: Jobs are scheduled on available spot GPUs with second-level billing.
- Optimized Inference Stack: Includes INT8/FP8 quantization, context caching, and dynamic batching cutting deployment time and reducing costs.
Who is Float16.cloud for?
Float16.cloud is suitable for:
- AI developers
- Machine learning engineers
- Researchers
- Anyone who needs GPU resources for AI model development and deployment
How to use Float16.cloud?
- Sign up for a Float16.cloud account.
- Upload your Python code or select an example.
- Configure the compute size and other settings.
- Launch your job and monitor its progress.
Pricing
Float16.cloud offers pay-per-use pricing with per-second billing. Spot pricing is also available for long-running jobs.
| GPU Types | On-demand | Spot |
|---|---|---|
| H100 | $0.006 / sec | $0.0012 / sec |
CPU & Memory are included, with free storage.
Security and Certifications
Float16.cloud has achieved SOC 2 Type I and ISO 29110 certifications. See the security page for details.
Conclusion
Float16.cloud simplifies AI development by providing serverless GPUs with true pay-per-use pricing. It's perfect for deploying LLMs, fine-tuning models, and running batch training jobs. With its easy-to-use interface and optimized performance, Float16.cloud helps you accelerate your AI projects and reduce costs.
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