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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.

4.4M visits/mo
Qoder logo
Qoder
✓ verifiedFreemium

Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.

2.7M visits/mo32K saves
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
Modal logo
Modal
✓ verifiedFreemium

Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.

988K visits/mo
Pricing

No public pricing

No public pricing

Free trial available

No public pricing

Starter: $0/mo + compute ($30 free credit)
Team: $250/mo + compute
Core features
  • Dialogue with GLM large model
  • AI search
  • AI drawing
  • AI reading
  • AI-generated video (沉思清影-AI生视频)
  • AI-generated PPT
  • Data analysis tools
  • Code assistance (代码速写)
  • Intelligent agents
  • Multi-agent collaboration for end-to-end tasks
  • Persistent memory and custom rules
  • Extensible skills and plugins
  • Rich context across code, images, and directories
  • Automatic codebase documentation generation
  • Terminal-native CLI and JetBrains IDE plugin
  • Cloud-hosted agents for enterprise use
  • 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
  • Serverless GPU compute defined in Python
  • Sub-second container cold starts
  • Autoscale 0 to 1000+ GPUs
  • Inference, training and batch workloads
  • Secure sandboxes for untrusted code
  • Built-in logging and observability
Use cases
  • Engaging in conversations with an AI model
  • Generating images and videos using AI
  • Creating presentations with AI assistance
  • Analyzing data with AI tools
  • Assisting with code development
  • Autonomous feature development in large codebases
  • Terminal-based AI pair programming
  • Cross-department task automation for legal, finance, HR
  • Onboarding developers to unfamiliar codebases
  • 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
  • Deploying and scaling model inference
  • Fine-tuning and training models
  • Running batch/parallel AI jobs
  • Executing untrusted code in sandboxes
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