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Pricing sourced from Fleek · Last verified March 2026
Both Fleek and Vercel offer edge deployment with global CDN distribution, but they differ significantly in scope and runtime support. Fleek adds decentralized infrastructure options (IPFS, Filecoin) and broader runtime support including Python and Rust, making it more suitable for diverse AI agent architectures. Vercel is more mature for Next.js and React applications with a larger ecosystem, while Fleek better supports Web3-integrated agents and Python-based frameworks like LangChain. For pure web app deployment, Vercel typically wins; for AI agents needing decentralized infrastructure or multi-runtime support, Fleek has the edge.
Fleek supports Python runtime for serverless functions, allowing deployment of Python-based agent frameworks like LangChain, AutoGen, CrewAI, or custom Python AI applications. The platform handles dependency installation through standard requirements.txt files, and you can deploy directly from GitHub repositories. Note that execution time and memory limits apply, so for long-running training or large model inference, you may need to pair Fleek with a dedicated compute platform like Modal or Replicate.
Fleek can store agent data and assets on IPFS (InterPlanetary File System) and Filecoin, providing immutable, content-addressed storage that's not controlled by any single entity. This is useful for censorship-resistant agents, blockchain-integrated AI applications, or scenarios where you need cryptographic proof that agent outputs haven't been tampered with. Most traditional AI agent use cases don't require these features — they're most valuable for crypto-native projects, autonomous agents in DAOs, or applications where decentralization is a core product requirement.
WebSocket support depends on the specific runtime and plan tier you're using on Fleek. For streaming AI responses (such as token-by-token LLM output), the platform's edge functions support standard HTTP streaming and Server-Sent Events, which work well for most chat and assistant interfaces. Persistent WebSocket connections may require Pro tier plans or specific configuration. Check Fleek's documentation at fleek.xyz/docs for the latest WebSocket capabilities.
Fleek's serverless functions have execution time, memory, and request size constraints that vary by plan tier — Free tier functions allow 10-second execution windows, Pro tier extends to 30 seconds, and Enterprise plans offer custom limits of 60+ seconds. For most AI agent workloads (a single LLM API call with response processing), these limits are sufficient. However, agents requiring multi-step reasoning, large context processing, or model fine-tuning will hit limits and need a hybrid architecture pairing Fleek edge endpoints with longer-running compute on platforms like Modal or AWS Lambda.
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