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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.

WaveSpeedAI logo
WaveSpeedAI
✓ verifiedFree trial

Pay-per-use API hub aggregating 1000+ image, video, and audio generation models for developers building AI media pipelines.

2.2M visits/mo
MuAPI logo
MuAPI
✓ verifiedPaid

Unified pay-per-generation API for 500+ image, video and audio models like FLUX, Kling and Seedance at low cost.

411K visits/mo
AI/ML API logo
AI/ML API
✓ verifiedPaid

Single API and playground for 1000+ AI models (chat, image, video, audio) with pay-as-you-go billing.

223K visits/mo5.7K saves
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
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
Pricing
Silver: $100 top-up (higher rate limits)
Gold: $1,000 top-up (higher rate limits)
Ultra: $10,000 top-up (highest rate limits)

Free trial available

No public pricing

Pay As You Go: $20 top-up (pay per use, all models)

Free trial available

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
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

Core features
  • Unified API access to 1000+ image/video/audio generation models
  • Pay-per-use pricing billed per image or per second of video
  • Includes chat/LLM model access (Claude, GPT, Gemini, etc.) priced per token
  • Account tiers unlock higher GPU limits and concurrency
  • CLI and desktop app for building workflows
  • Enterprise options with dedicated support and custom deployment
  • Single API for 500+ image, video and audio models
  • Pay-per-generation billing with no subscription
  • No charge on failed tasks
  • Workflows, agents and studio tools
  • MCP and CLI integrations, white-label option
  • One API for 1000+ models
  • OpenAI/Anthropic-compatible endpoints
  • Chat, image, video, audio and embedding models
  • AI playground/sandbox
  • Pay-as-you-go billing across models
  • Enterprise dedicated infrastructure option
  • 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
  • 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
Use cases
  • Integrating AI image/video generation into an app via API
  • Building automated content pipelines needing multiple AI models
  • Testing and comparing many generative models from one account
  • Scaling AI media production with volume-based account tiers
  • Accessing both media-generation and LLM APIs from one platform
  • Building apps on top of many generative models via one API
  • Generating images, video and audio at scale
  • Cutting model API costs versus direct providers
  • Deploying white-label AI generation studios
  • Integrating many AI models via one API
  • Prototyping and scaling AI apps
  • Cost-controlled multi-model access
  • Serving open models in production apps and agents
  • Fine-tuning models on private data
  • Powering code assistants, chatbots and RAG at scale
  • 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
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