Float16.Cloud

Float16.Cloud: Serverless GPUs for Accelerated AI Development

What is Float16.Cloud?

Float16.Cloud is a serverless GPU platform designed to accelerate AI development. It allows users to instantly run, train, and scale AI models without the complexities of infrastructure setup. This platform offers ready-to-run environments, full control over code, and a seamless developer experience.

How does Float16.Cloud work?

Float16.Cloud simplifies AI development by providing serverless GPUs that eliminate the need for manual server configuration. Key features include:

• Fast GPU Spin-Up: Get compute resources in under a second with preloaded containers ready for AI and Python development.
• Zero Setup: Avoid the overhead of Dockerfiles, launch scripts, and DevOps. Float16 automatically provisions and configures high-performance GPU infrastructure.
• Spot Mode with Pay-Per-Use: Train, fine-tune, and batch process on affordable spot GPUs with per-second billing.
• Native Python Execution on H100: Run Python scripts directly on NVIDIA H100 GPUs without building containers or configuring runtimes.

Key Features and Benefits

• Serverless GPU Infrastructure:

  • Run and deploy AI workloads instantly without managing servers.
  • Containerized infrastructure for efficient execution.

• H100 GPUs:

  • Leverage NVIDIA H100 GPUs for high-performance computing.
  • Ideal for demanding AI tasks.

• Zero Setup:

  • No need for Dockerfiles, launch scripts, or DevOps overhead.
  • Focus on coding, not infrastructure management.

• Pay-Per-Use Pricing:

  • Per-second billing on H100 GPUs.
  • Pay only for what you use, with no idle costs.

• Native Python Execution:

  • Run .py scripts directly on NVIDIA H100 without building containers or configuring runtimes.
  • Containerized and GPU-isolated execution.

• Full Execution Trace & Logging:

  • Access real-time logs and view job history.
  • Inspect request-level metrics, task counts, and execution duration.

• 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.
  • Examples range from model inference to batched training loops.

• CLI-First, Web-Enabled:

  • Manage everything from the command line or monitor jobs from the dashboard.
  • Both interfaces are tightly integrated.

• Flexible Pricing Modes:

  • On-demand for short bursts.
  • Spot pricing for long-running jobs like training and fine-tuning.

• Serve Open-Source LLMs:

  • Provision a high-performance LLM server from a single CLI command.
  • Production-ready HTTPS endpoint.
  • Run any GGUF-based model like Qwen, LLaMA, or Gemma.
  • Sub-second latency, no cold starts.

• Finetune and Train:

  • Execute training pipelines on ephemeral GPU instances using your existing Python codebase.
  • Spot-optimized scheduling.
  • Zero setup environment with automatic CUDA drivers and Python environment setup.

Use Cases

• Serving Open-Source LLMs: Quickly deploy open-source LLMs via llamacpp, with a production-ready HTTPS endpoint.
• Fine-tuning and Training: Execute training pipelines on spot GPUs using existing Python code.

How to use Float16.Cloud?

1. Sign Up: Create an account on Float16.Cloud.
2. Access the Dashboard: Navigate to the web dashboard or use the CLI.
3. Upload Code: Upload your Python scripts or models.
4. Select GPU Type: Choose between on-demand or spot GPUs.
5. Run Workload: Execute your AI tasks and monitor progress via logs and metrics.

Why choose Float16.Cloud?

Float16.Cloud is ideal for users who want to:

• Accelerate AI development without managing infrastructure.
• Reduce costs with pay-per-use pricing and spot instances.
• Simplify deployment with pre-configured environments and native Python execution.
• Scale AI workloads efficiently.

Who is Float16.Cloud for?

Float16.Cloud is designed for:

• AI/ML Engineers: Accelerate model development and deployment.
• Data Scientists: Focus on data analysis and model building without infrastructure concerns.
• Researchers: Run experiments and train models at scale.
• Startups: Quickly deploy AI applications without significant upfront investment.

Float16.Cloud simplifies the process of deploying and scaling AI models by providing serverless GPUs, a user-friendly interface, and cost-effective pricing. Its features cater to the needs of AI engineers, data scientists, and researchers, making it an excellent choice for those looking to accelerate their AI development workflows.