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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
SiliconFlow logo
SiliconFlow
✓ verified

Developer platform serving 200+ optimized LLMs via APIs; high traffic.

434K visits/mo1.1K 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
Replicate AI logo
Replicate AI
✓ verifiedPaid

Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.

1.3M visits/mo17K saves
Atlas Cloud logo
Atlas Cloud
✓ verifiedPaid

Unified pay-per-use API serving 400+ multimodal AI models (image, video, audio, 3D, LLM) through one OpenAI-compatible key.

958K 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

No public pricing

No public pricing

CPU (Small): $0.000025/sec ($0.09/hr)
Nvidia A100 80GB: $0.0014/sec ($5.04/hr)
Nvidia H100: $0.001525/sec ($5.49/hr)

Free trial available

Seedance 2.0 video: from $0.09/sec
GPT Image 2: from $0.009/image
Nano Banana 2: from $0.04/image
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
  • Access over 200 optimized models, including LLMs, image, video, and audio processing.
  • Achieve low-latency, high-throughput inference with SiliconFlow's self-developed acceleration frameworks.
  • Deploy models via serverless inference, dedicated endpoints, or reserved GPUs to suit various workloads.
  • Customize models to your data with built-in monitoring and elastic compute resources.
  • Ensure data privacy and business security with dynamic scaling and fault tolerance mechanisms.
  • 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
  • One-line API calls to run community and proprietary AI models
  • Support for image, video, speech, and LLM generation models
  • Fine-tuning and custom model deployment via Cog
  • Per-second usage billing on shared or dedicated hardware
  • Automatic scaling for high-traffic private models
  • Thousands of community-published models with production APIs
  • 400+ AI models via one unified API
  • Multimodal coverage: image, video, audio, 3D, LLM
  • On-demand, pay-per-use pricing
  • Day-0 access to new state-of-the-art models
  • OpenAI-compatible single key
  • SOC 2 and HIPAA compliance, 99.99% uptime
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
  • Quickly deploy various AI models via a simple API, supporting tasks like text, image, audio, and video processing.
  • Utilize serverless GPUs to automatically scale AI applications, ensuring flexibility and cost-efficiency.
  • Access high-performance GPUs for demanding workloads, such as large-scale inference and video generation.
  • Deploy custom models with guaranteed performance and scalability, tailored to specific business needs.
  • 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
  • Developers embedding image/video/speech generation into an app via API
  • Teams deploying and scaling their own fine-tuned models
  • Builders comparing outputs from multiple AI models in one playground
  • Companies avoiding GPU infrastructure management for ML inference
  • Integrate video and image generation
  • Access many LLMs through one API
  • Build multimodal AI applications
  • Batch generate and prototype cheaply
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