AgentQuote
Estimate the cost of running your AI agent system
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About AgentQuote
AgentQuote helps AI agencies and developers estimate how much their AI agent systems will cost to run, before they quote clients or commit to an architecture. Describe your system in plain English (agents, tools, models, volume) and get: - Cost estimates across 3 scenarios (light, normal, heavy usage) - Architecture review that flags what's costing you the most - Personalized optimization recommendations with dollar savings - Per-agent cost breakdowns showing where tokens accumulate Every formula is built on real experimental data, not theoretical pricing page math. We measured multi-agent overhead (4.8x), caching savings (90%), loop detection impact (49%), and memory strategy tradeoffs across 8 architecture patterns. Free. No signup. No paywall.
Product Insights
AgentQuote is a web-based developer tool that provides data-driven cost estimation and architecture reviews for AI agent systems across varied usage scenarios. The platform leverages experimental data from multiple architecture patterns to identify token accumulation points and optimization opportunities.
- Utilizes real experimental data rather than theoretical pricing page math for high-accuracy projections.
- Provides multi-scenario cost estimates covering light, normal, and heavy usage patterns.
- Identifies specific high-cost components within agent architectures through per-agent breakdowns.
- Available as a free web service with no signup or paywall requirements for immediate access.
Ideal for: Agencies, developers, and founders require these cost projections to quote clients accurately and refine architecture before committing to expensive production deployments.
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Comments (2)
This looks interesting! Would be nice to add Gemini models too. Generally, more recent ones (GPT-5.4, Sonnet-4.6, etc.)
Built this after discovering multi-agent AI systems cost 4.8x more than single agents, and most agencies find out after they've already quoted the client. Every formula comes from real token-level ex