toolspool

Compare tools

Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Nebius logo
Nebius
✓ verifiedPaid

AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.

678K visits/mo133K saves
Google Antigravity logo
Google Antigravity
✓ verifiedFree

Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.

22M visits/mo18K saves
Manus logo
Manus
✓ verifiedFreemium

General-purpose autonomous AI agent that plans and runs multi-step tasks such as building sites, slides and research in the cloud.

28M visits/mo89K saves
Glean logo
Glean
✓ verifiedPaid

Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.

3.2M visits/mo
Pricing
NVIDIA H100: $3.85/GPU-hour on-demand ($2.15 preemptible)
NVIDIA H200: $4.50/GPU-hour on-demand
NVIDIA B200: $7.15/GPU-hour on-demand
Shared filesystem storage: $0.08/GiB per month

No public pricing

No public pricing

No public pricing

Core features
  • NVIDIA GPU instances (H100, H200, B200, GB200)
  • On-demand and preemptible GPU pricing
  • High-performance and object storage
  • Managed Kubernetes and Slurm (Soperator)
  • Serverless and managed inference (Token Factory)
  • MLOps tooling and 24/7 expert support
  • Commitment discounts up to 35%
  • Agent-first IDE experience
  • Autonomous planning and code execution
  • Integrated editor, terminal and browser control
  • Powered by Google's Gemini models
  • High-level developer supervision
  • Autonomous multi-step task execution
  • Website and app building
  • AI slides, design and image generation
  • Manus browser operator
  • Wide Research mode
  • Cross-platform web, desktop and mobile apps
  • Enterprise search across company apps
  • Personal AI assistant grounded in work data
  • Agent builder, orchestration and governance
  • 250+ connectors and actions
  • Enterprise knowledge graph and hybrid search
  • Security controls for scaling AI
Use cases
  • Train large AI/ML models on GPU clusters
  • Run scalable inference workloads
  • Store and manage large training datasets
  • Run Slurm/Kubernetes AI pipelines
  • Building apps with AI agents
  • Automating multi-step coding tasks
  • Prototyping and iterating on software
  • Assisting developers on complex work
  • Automate end-to-end digital tasks
  • Produce websites and presentations
  • Conduct broad research
  • Hand off browser tasks to an agent
  • Search across all company knowledge
  • Answer employee questions with grounded AI
  • Build and deploy custom AI agents
  • Automate cross-system workflows
Visit
More in AI Agents Infrastructure