Beam vs Arcade AI

Detailed side-by-side comparison to help you choose the right tool

Beam

🔴Developer

AI Infrastructure

Beam is AI infrastructure for developers: serverless sandboxes, task queues, and GPU model inference with sub-second cold starts and per-second billing. It is a Modal/RunPod competitor focused on AI primitives like vLLM, ComfyUI, and agent code sandboxing.

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Arcade AI

🔴Developer

AI Infrastructure

Arcade AI is an MCP runtime for production agents focused on secure tool authorization, hosted MCP servers, and authenticated SaaS actions.

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Feature Comparison

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FeatureBeamArcade AI
CategoryAI InfrastructureAI Infrastructure
Pricing Plans8 tiers6 tiers
Starting Price
Key Features
    • • MCP runtime for secure, reliable production AI agent deployments
    • • Connects identity providers, enforces agent authorization, and enables actions in Google, Slack, and Salesforce
    • • Hobby plan includes 100 user challenges, 1,000 standard tool executions, 50 pro executions, and one hosted MCP server

    Beam - Pros & Cons

    Pros

    • ✓Publicly itemized per-second GPU pricing is unusually transparent for the category
    • ✓Sandboxes for agent-generated code are a first-class primitive, not an afterthought
    • ✓Single decorator gets a Python function onto a GPU with HTTPS in front of it

    Cons

    • ✗Usage-based billing can spike fast under unbounded autoscale — set alerts day one
    • ✗Less general-purpose than Modal if you also want non-AI batch workflows
    • ✗$30 free credit burns quickly on H100s — evaluation budget is smaller than it looks

    Arcade AI - Pros & Cons

    Pros

    • ✓Clear differentiation: focuses on authenticated tool use and enterprise-ready MCP runtime, not generic workflow automation
    • ✓Transparent pricing with a usable free Hobby tier and published Growth usage allowances
    • ✓Strong fit for developers building agents that must safely act in SaaS tools

    Cons

    • ✗Developer infrastructure product; non-technical teams will need engineering support to implement it well
    • ✗Usage-based pricing requires monitoring once agents run many authenticated actions
    • ✗The value depends on whether your agent roadmap actually needs MCP-compatible tool execution

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