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

BoltAI logo
BoltAI
✓ verifiedPaid

Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.

81K visits/mo33K saves
Nebius logo
Nebius
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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
Vast ai logo
Vast ai
✓ verifiedPaid

GPU rental marketplace with per-second billing across thousands of GPUs, aimed at AI training, inference, and fine-tuning workloads.

1.4M visits/mo
Pricing
Essential: $79 (1 seat, one-time)
Pro: $99 (2 seats + 1 mobile, one-time)
Team Perpetual: $99/seat/year

Free trial available

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

Core features
  • Switch across 300+ hosted and local AI models
  • Native macOS app with global shortcut and screenshot-to-answer
  • Reusable agents, projects, and forked chats
  • Multimodal analysis of PDFs, images, and code
  • MCP tools and code execution
  • Local chat storage with encryptable API keys
  • 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%
  • On-demand GPU cloud with per-second billing
  • Interruptible instances at discounted rates for batch/fault-tolerant jobs
  • Reserved capacity with 1, 3, or 6-month terms for steady workloads
  • Serverless deployment with autoscale-to-zero for inference endpoints
  • Dedicated multi-node clusters with InfiniBand for large-scale training
  • Python SDK and CLI plus REST API for programmatic provisioning
  • Access to 68+ GPU types across 40+ data centers
  • Pre-configured templates for popular open-source models
Use cases
  • Using multiple AI providers in one place
  • Explaining or fixing on-screen content instantly
  • Building reusable task-specific agents
  • Analyzing documents and screenshots privately
  • Train large AI/ML models on GPU clusters
  • Run scalable inference workloads
  • Store and manage large training datasets
  • Run Slurm/Kubernetes AI pipelines
  • ML engineers training or fine-tuning models on rented GPUs
  • Startups running inference at scale without owning hardware
  • Developers needing quick, low-cost access to specific GPU types
  • Teams building AI agents that autonomously provision compute
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