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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.

SiliconFlow logo
SiliconFlow
✓ verified

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

434K visits/mo1.1K saves
PicoClaw logo
PicoClaw
✓ verifiedFree

Ultra-lightweight, self-hosted open-source AI assistant in Go that runs on sub-$10 hardware like Raspberry Pi with under 10MB RAM.

81K visits/mo
LLM Gateway logo
LLM Gateway
✓ verifiedFreemium

Unified API and gateway routing requests across 200+ models from 40+ providers, with cost tracking and a free BYOK tier.

76K visits/mo
Claude logo
Claude
✓ verifiedFreemium

Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.

22M visits/mo231K saves
OpenRouter logo
OpenRouter
✓ verifiedFreemium

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

17M visits/mo
Pricing

No public pricing

No public pricing

Free: $0 forever (BYOK)
Pay-as-you-go: 5% fee on credit usage

Free trial available

Free: $0
Pro: $17/month billed annually ($200 up front), or $20/month
Max: From $100/month
Team: $20/seat/month billed annually ($25 monthly); premium seats $100/seat/month annually ($125 monthly)
Enterprise: Contact sales
Free: $0
Pay-as-you-go: Per-token, no subscription
Enterprise: Talk to sales
Core features
  • 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.
  • Single self-contained binary requiring under 10MB RAM
  • Sub-1-second startup even on low-power processors
  • Support for 16+ chat channels including Telegram, Discord, Slack, WeCom
  • Compatibility with multiple LLM providers (OpenAI, Claude, DeepSeek, Gemini, etc.)
  • Runs on Raspberry Pi, RISC-V, ARM64, x86_64, Android, and Docker
  • Self-hosted design keeping data and configuration local
  • Gateway/API mode for connecting to chat platforms via MCP protocol
  • One API for 200+ models across 40+ providers
  • Provider switching without code changes
  • Real-time cost tracking
  • Bring-your-own-keys, free forever
  • Observability and guardrails
  • SOC 2 Type II certified
  • Conversational writing and editing
  • Code generation and debugging (Claude Code)
  • Data analysis and visualization
  • Web search plus memory across chats
  • Connectors and remote MCP integrations
  • Extended thinking for complex tasks
  • 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
Use cases
  • 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.
  • Running a private AI assistant on minimal or embedded hardware
  • Local code assistance that keeps proprietary code off the cloud
  • Home automation and personal task scheduling via chat bots
  • Privacy-conscious users wanting self-hosted AI on low-cost devices
  • Route across many LLM providers from one API
  • Track and control AI spend
  • Avoid vendor lock-in with provider switching
  • Drafting and refining written content
  • Building and debugging software
  • Analyzing datasets for insights
  • Research and learning support
  • Team and enterprise automation
  • Accessing many LLMs through one integration
  • Adding provider redundancy to AI apps
  • Comparing model price and performance
  • Powering agents and AI-native products
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