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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.

OpenRouter logo
OpenRouter
✓ verifiedFreemium

Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.

17M 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
Manus logo
Manus
✓ verifiedFreemium

General-purpose autonomous AI agent that plans and runs multi-step tasks such as building sites, slides and research in the cloud.

28M visits/mo89K saves
Lightning  AI logo
Lightning AI
✓ verifiedFreemium

Cloud platform from the makers of PyTorch Lightning for building, training and deploying AI in browser-based GPU Studios.

467K visits/mo3.8K saves
Unsloth AI logo
Unsloth AI
✓ verifiedFreemium

Open-source library and desktop app for fast, memory-efficient local fine-tuning and inference of open LLMs.

1.1M visits/mo29K saves
Pricing
Free: $0 (free models only, 50 requests/day)
Pay-as-you-go: 5.5% platform fee on inference

No public pricing

Free trial available

No public pricing

No public pricing

No public pricing

Core features
  • One unified, OpenAI-compatible API for 400+ models
  • Automatic provider failover for higher uptime
  • Edge routing for low latency
  • Custom data and provider policies
  • Pay-as-you-go credits usable across any model
  • 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
  • Autonomous multi-step task execution
  • Website and app building
  • AI slides, design and image generation
  • Manus browser operator
  • Wide Research mode
  • Cross-platform web, desktop and mobile apps
  • Browser-based Lightning Studios with on-demand GPUs
  • PyTorch Lightning training framework
  • Model training, fine-tuning and deployment
  • Collaborative, shareable ML environments
  • Scalable multi-GPU/multi-node compute
  • Optimized LoRA/FFT/PT training kernels for 500+ models
  • Local offline model runner for Mac and Windows
  • No-code dataset creation from PDFs, CSVs, and JSON
  • Unlimited tool-calling and web search inside model runs
  • Data Recipes workflow to turn documents into training datasets
  • Export to safetensors or GGUF for llama.cpp, vLLM, Ollama
  • Multi-GPU support on paid tiers
Use cases
  • Accessing many LLMs through one integration
  • Adding provider redundancy to AI apps
  • Comparing model price and performance
  • Powering agents and AI-native products
  • Autonomous feature development in large codebases
  • Terminal-based AI pair programming
  • Cross-department task automation for legal, finance, HR
  • Onboarding developers to unfamiliar codebases
  • Automate end-to-end digital tasks
  • Produce websites and presentations
  • Conduct broad research
  • Hand off browser tasks to an agent
  • Prototype and train ML models in the cloud
  • Fine-tune and deploy foundation models
  • Run reproducible AI experiments collaboratively
  • ML engineers fine-tuning open models on a single GPU for free
  • Teams building custom datasets from unstructured documents
  • Developers wanting to run and compare LLMs fully offline
  • Enterprises needing faster, more accurate multi-node training
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