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Pick 2–5 published tools. Values come from our evidence-checked profiles — an em-dash means unknown, never “no”. Ranking rows reflect the current published methodology for the comparison context.
Requesty vs Cloudflare AI Gateway
Context: LLM Gateways & Model Routing Platforms · 16 rows
| Attribute | RequestyRequesty | Cloudflare AI GatewayCloudflare |
|---|---|---|
| Identity · Taxonomy | ||
| Documentation | https://docs.requesty.ai | https://developers.cloudflare.com/ai-gateway/ |
| Tags | llm-gateway, model-routing, cost-optimization, observability | llm-gateway, proxy, caching, rate-limiting, analytics |
| Platform · Deployment | ||
| Delivery model | SaaS | SaaS |
| Pricing · Licensing | ||
| Free plan | true | true |
| Pricing model | usage, custom | free, subscription, usage |
| Features · Product · Fit | ||
| Core capabilities | OpenAI-compatible router API for 600+ models, Routing by cost, latency, and availability, Automatic failover and weighted load balancing, Observability dashboards for cost and latency, RBAC and approved-model whitelists, PII masking with EU data residency | Provider proxying for AI applications, Response caching, Rate limiting, Request retry and model fallback, Analytics for requests, tokens, and cost, Logging of requests and errors |
| Api · Integrations · Ecosystem | ||
| API available | true | true |
| Security · Privacy · Compliance | ||
| Regulatory compliance | GDPR | — |
| Audience · Use · Case | ||
| Best for | Developers and companies that want a hosted router across many model providers with cost controls, caching, and governance features. | Teams that want AI gateway controls such as caching, rate limits, analytics, and fallbacks across model providers, especially those already using Cloudflare. |
| Company-size fit | individual, SMB, mid-market, enterprise | individual, SMB, mid-market, enterprise |
| Primary use cases | Multi-provider LLM routing, Cost optimization and budget caps, AI governance and PII protection | Cost tracking for LLM usage, Rate limiting AI traffic, Caching model responses, Provider failover |
| Skill level | intermediate | intermediate |
| Lifecycle · Versioning | ||
| Maintenance status | active | active |
| Vendor · Maintainer | ||
| Founded year | — | 2009 |
| Headquarters country | — | United States |
| Vendor type | commercial | commercial |
“—” means unknown (we never treat missing evidence as a negative). Cells reflect each value's current evidence state; superseded or stale values are excluded. Ranking rows are editorial assessments under the cited methodology version — see the LLM Gateways & Model Routing Platforms category for definitions.