Float16
Float16.cloud is a platform offering AI as a service. The tool does not create vendor lock-in and aims to support the building of AI produc...
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What is Float16?
Float16 is a full-stack GPU management platform designed specifically for AI and machine learning workloads. It provides one platform to deploy, manage, and scale entire GPU infrastructure, from ready-to-use AI services to bare-metal GPU instances. The platform offers three service tiers: AI-as-a-Service (AaaS) for instant access to ready-to-use AI models without coding or infrastructure knowledge, Platform-as-a-Service (PaaS) for developers building AI products, and Infrastructure-as-a-Service (IaaS) for bare-metal GPU instances.
Key features include Serverless GPU with scale-to-zero capability and 1-second cold start for ML Engineers, dedicated GPU resources with zero interference (each GPU is isolated with no noisy neighbors), one-click deployment that reduces setup time from 2+ weeks to just 5 minutes, credit-based quotas instead of fixed time slots for flexible resource allocation, and pre-configured ML training environments for NVIDIA TAO, MONAI, and NeMo. The platform also offers LLM endpoints with ready-to-use APIs, Jupyter Notebook access for researchers, and secure shell remote access for data scientists.
Float16 is ideal for ML Engineers who need serverless GPU scaling, Researchers doing teaching and proof-of-concept work, Data Scientists requiring full control via secure shell, Developers building AI products needing ready-to-use API endpoints, and teams new to the LLM industry who lack resources for experimentation. The platform supports popular models like Llama, Mistral, Qwen, SeaLLM, and SQLCoder, with OpenAI-compatible API integration.
The platform achieves 90%+ GPU utilization, offers enterprise-grade security, provides 24/7 support, and achieves 80% TCO reduction compared to traditional setups. Float16 is backed by NVIDIA's Inception Program and partners including Typhoon and SCB10X.
Float16 pricing
Pricing model: Free
Float16 uses pay-per-compute and pay-as-you-go pricing where users are billed only for actual compute time used. GPU instances are priced 50-70% less than major cloud providers. LLM as a Service charges per million tokens: SeaLLM-7b-v2.5 at $0.2 per million tokens and SQLCoder-7b-2 at $0.6 per million tokens. The platform offers credit-based quotas instead of fixed time slots for flexible team usage. Transparent pricing with pay only for what you use. No free tier is explicitly mentioned; users need to sign up for a Float16 App account to begin using services.
Float16 pros
- 50-70% cheaper than major cloud providers
- One-click deployment in 5 minutes vs 2+ weeks
- Serverless GPU with scale-to-zero capability
- 1-second cold start time
- Dedicated GPU resources with zero interference
- No noisy neighbors or resource contention
- OpenAI-compatible API for easy integration
- Credit-based quotas instead of fixed time slots
- 90%+ GPU utilization rate
- 80% TCO reduction
- Zero DevOps required
- Pre-configured ML training environments
- Support for H100 GPU instances
- Enterprise-grade security
- 24/7 support available
- Intuitive dashboard and API
- No complex configurations required
- Built specifically for AI workloads
- Low-latency networking for distributed training
- High-speed NVMe storage for datasets
Float16 cons
- Primarily focused on AI/ML workloads only
- Newer provider with less established track record
- Limited documentation compared to major providers
- Fewer GPU options than AWS or Google Cloud
- No free tier mentioned on website
- Private hosting requires contacting sales
- API key still required despite simplicity claims
- Port range limited to 3000-4000 for vLLM
- No multi-region deployment mentioned
- Limited enterprise features compared to established clouds
Frequently asked questions about Float16
What is Float16 Cloud?
Float16 Cloud is a GPU cloud platform designed specifically for AI and machine learning workloads. It provides easy access to high-performance NVIDIA GPUs at competitive prices, offering GPU instances for training and inference, serverless deployment without managing infrastructure, ready-to-use AI services like LLM inference and OCR, pre-configured ML training environments, and one-click deployment for popular models.
How much cheaper is Float16 compared to major cloud providers?
Float16 GPU instances are priced competitively, often 50-70% less than major cloud providers like AWS, Google Cloud, or Azure. This cost advantage comes from efficient resource utilization and optimized infrastructure specifically built for AI workloads.
What is Serverless GPU and how does it work?
Serverless GPU is a service that enables users to run, train, or deploy AI models and Python code without managing infrastructure. It scales to zero when not in use and has a 1-second cold start time. Users are billed only for actual compute time used through a pay-per-compute model, making it cost-effective and flexible for ML Engineers.
What models can I deploy on Float16?
Float16 supports popular open-source models including Llama, Mistral, Qwen, SeaLLM-7b-v2.5, SQLCoder-7b-2, GPT-OSS-120B, Gemma, RecurrentGemma, and Mamba. Users can deploy these via one-click deployment or custom deployment with OpenAI-compatible API endpoints.
How do I access the API for deployed models?
Float16 provides OpenAI-compatible API access. The endpoint format is https://proxy-instance.float16.cloud/{instance_id}/3900/v1 for vLLM deployments. You authenticate by setting api_key to any value (not actually required). Available endpoints include /v1/chat/completions for chat generation, /v1/models for listing models, and /v1/health for health checks.
What ML training frameworks are pre-configured?
Float16 offers pre-configured environments for NVIDIA TAO 6.x (computer vision model training), MONAI 1.5.1 (medical imaging AI), and NeMo 2.6.1 (speech and conversational AI). These ready-to-use environments eliminate complex configuration setup.
How does credit-based quota work compared to fixed time slots?
Instead of locking teams to specific hours (e.g., 8AM-2PM), Float16 gives teams credit-based quotas they can use flexibly whenever needed. This achieves 100% GPU utilization versus 67% with fixed slots, eliminates wasted reserved time, and allows dynamic allocation based on workload type (training, inference, batch processing) with optimized configurations for each.
What AI Services are available beyond LLM?
Beyond LLM deployment, Float16 offers Typhoon OCR for extracting text from Thai and English documents, vLLM Playground for testing models with tool calling and structured outputs, and ready-to-use APIs for OCR and other AI capabilities without managing infrastructure.
Do I need DevOps knowledge to use Float16?
No DevOps knowledge is required. Float16 eliminates infrastructure complexity with one-click deployment in 5 minutes, intuitive dashboard, pre-configured environments, and managed services. The platform achieves zero DevOps requirement, allowing developers to focus on building rather than infrastructure management.
How do I get started with Float16?
To begin using Float16, sign up for a Float16 App account at float16.cloud. Once registered, navigate to GPU Instances or LLM as a Service in the dashboard. For LLM API access, use curl with your float16-api-key and select a model like SeaLLM-7b-v2.5. For documentation, visit docs.float16.cloud. Contact [email protected] or join their Discord community for assistance.