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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.
Kong AI Gateway vs Cloudflare AI Gateway
Context: LLM Gateways & Model Routing Platforms · 18 rows
| Attribute | Kong AI GatewayKong | Cloudflare AI GatewayCloudflare |
|---|---|---|
| Identity · Taxonomy | ||
| Documentation | https://developer.konghq.com/ai-gateway/ | https://developers.cloudflare.com/ai-gateway/ |
| Tags | llm-gateway, api-gateway, kubernetes, mcp, microservices | llm-gateway, proxy, caching, rate-limiting, analytics |
| Platform · Deployment | ||
| Delivery model | SaaS, self-hosted | SaaS |
| Pricing · Licensing | ||
| Free plan | — | true |
| License model | open-source | — |
| Pricing model | custom | free, subscription, usage |
| Source repository | https://github.com/Kong/kong | — |
| SPDX license IDs | Apache-2.0 | — |
| Features · Product · Fit | ||
| Core capabilities | Multi-LLM routing with provider failover, Semantic caching and load balancing, PII sanitization and semantic prompt guards, Token quotas, chargeback, and spend tracking, MCP server governance and authentication, L7 observability with logging and tracing | 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 |
| Audience · Use · Case | ||
| Best for | Organizations with existing API gateway or Kubernetes infrastructure that want LLM, MCP, and agent traffic governed through one gateway platform. | 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 | SMB, mid-market, enterprise | individual, SMB, mid-market, enterprise |
| Primary use cases | Governing LLM traffic in API infrastructure, MCP and agent-to-agent traffic governance, Provider switching and failover | Cost tracking for LLM usage, Rate limiting AI traffic, Caching model responses, Provider failover |
| Skill level | advanced | 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.