Cloudflare AI Gateway vs AgentHost
Detailed side-by-side comparison to help you choose the right tool
Cloudflare AI Gateway
App Deployment
Cloudflare AI Gateway is a free AI observability and control layer that proxies requests to OpenAI, Anthropic, Google, and 25+ providers with caching, rate limiting, logging, DLP, and Guardrails.
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Starting Price
FreeAgentHost
🔴DeveloperApp Deployment
Serverless hosting platform specifically designed for deploying and scaling AI agents.
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Starting Price
$49/monthFeature Comparison
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Cloudflare AI Gateway - Pros & Cons
Pros
- ✓Core features are genuinely free on every Cloudflare account — analytics, caching, rate limiting, DLP, persistent logs
- ✓One line of code change works with existing OpenAI, Anthropic, and Google SDKs across 25+ providers
- ✓Runs on Cloudflare's edge so proxy latency overhead is single-digit milliseconds globally
Cons
- ✗Log retention is capped per plan (100k Free / 10M per gateway Paid) — not unlimited
- ✗Span-level observability and evals are thinner than Langfuse or Helicone
- ✗Dynamic Routing, Spend Limits, and BYOK are still beta with documented rough edges
AgentHost - Pros & Cons
Pros
- ✓Purpose-built persistent memory layer that the company claims delivers up to 40% faster context retrieval than standard database-backed solutions
- ✓Kernel-level sandboxing with granular network egress controls lets agents safely execute untrusted code
- ✓NVIDIA H100 and A100 GPU clusters available for local inference on open-weight models (128 new H100 nodes added Feb 2026)
- ✓Pro plan at $99/month bundles 5 agent instances, 16GB RAM, and 100GB SSD — cheaper than equivalent AWS setup (~$93/month before memory/sandbox config)
- ✓Full SSH access and framework-agnostic deployment — not locked into a proprietary flow
- ✓Pre-built templates for AutoGPT, LangChain, CrewAI, and AutoGen speed up production deployment
Cons
- ✗No free tier — minimum commitment is $49/month, unlike Modal which starts at $0 pay-per-use
- ✗Starter plan's 8GB RAM and single instance is tight for agents running local models or large context windows
- ✗Relatively new platform means a thinner track record and smaller community than AWS, GCP, or Azure
- ✗Limited geographic regions compared to hyperscalers may affect global latency for some deployments
- ✗Specialized infrastructure creates vendor risk — migrating off agent-specific features requires reengineering
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