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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.

Fireworks AI logo
Fireworks AI
✓ verifiedPaid

Developer platform for fast serverless inference and training of open generative models, billed per token or GPU-second.

611K visits/mo1.3K 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
CometAPI logo
CometAPI
✓ verifiedPaid

Unified API to 500+ AI models (OpenAI, Anthropic, Google, etc.) with OpenAI-compatible calls priced ~20% below official rates.

363K visits/mo4.8K saves
Evolink AI Model API logo
Evolink AI Model API
✓ verifiedPaid

One API to access leading LLM, image, video, and audio models with pay-as-you-go, usage-based pricing.

363K visits/mo1.5K saves
Kiro AI logo
Kiro AI
✓ verifiedFreemium

Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.

3.8M visits/mo
Pricing
On-Demand H100/H200: $7/GPU-hour
On-Demand B200: $10/GPU-hour
On-Demand B300: $12/GPU-hour
Fine-tuning (LoRA SFT, models up to 16B): from $0.50 per 1M training tokens

No public pricing

Pay-as-you-go, min top-up $10
GPT-5.6: $4 / 1M tokens
Claude Sonnet 5: $1.6 / 1M tokens

Free trial available

Usage-based pay-as-you-go (e.g., Seedance 2.0 $0.198/s, GPT Image 2 from $0.015/image)
Free: $0/mo (50 credits)
Pro: $20/user/mo (1,000 credits)
Pro+: $40/user/mo (2,000 credits)
Pro Max: $100/user/mo (5,000 credits)
Power: $200/user/mo (10,000 credits)
Core features
  • Serverless per-token inference with OpenAI/Anthropic-compatible APIs
  • On-demand dedicated and reserved GPU deployments
  • Fine-tuning and reinforcement-learning training pipelines
  • Large library of open LLM, vision, image and audio models
  • Optimized inference engine for throughput and latency
  • 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 key for 500+ models
  • OpenAI-compatible API
  • Pay-as-you-go credits (~20% below list)
  • Multimodal: text, image, video, audio
  • Usage analytics and budget alerts
  • Integrations (Claude Code, n8n, Zapier, etc.)
  • Single API for LLM, image, video, and audio models
  • Access to GPT, Claude, Gemini, Seedance, and more
  • Usage-based, pay-as-you-go pricing
  • Model comparison and documented capabilities
  • Smart Router for model selection
  • 99.9% uptime, no credit card to start
  • Spec-driven development (requirements, design, tasks)
  • Parallel agents, local or cloud
  • Property-based and correctness testing
  • Works in IDE, CLI, web and mobile
  • Multiple models (Claude, open-weight, Auto)
  • Headless CLI for CI/CD
  • Context from tools like Figma and Terraform
Use cases
  • Serving open models in production apps and agents
  • Fine-tuning models on private data
  • Powering code assistants, chatbots and RAG at scale
  • 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
  • Consolidating multi-provider AI billing
  • Switching models without re-integration
  • Powering apps and automation pipelines
  • Benchmarking models in one playground
  • Add multiple AI models to a product via one API
  • Switch between model providers without rewrites
  • Generate video, images, and audio programmatically
  • Build AI agents and workflows
  • Turning prompts into maintainable, spec-matched code
  • Catching bugs unit tests miss
  • Reviewing PRs and fixing bugs in CI/CD
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