Kong AI Gateway vs Apache APISIX AI Gateway

The question that decides it: Do you need LLM-native features and compliance paperwork, or is free and fast with basic proxying enough?

Our verdict

Already running Kong and need semantic caching, PII sanitization and guardrails on AI traffic: Kong, and accept that you will negotiate the price. Already running APISIX and need basic multi-provider proxying with retries and token rate limits: APISIX, free and permanently so.

Why

Neither of these is an LLM-first product. Both are mature API gateways — Kong on NGINX/OpenResty with 44,100 GitHub stars, APISIX also OpenResty-based with 16,800 — that grew AI plugins. You would choose either because you already run it for your regular API traffic and want AI requests governed by the same gateway, plugins and ops tooling. Adopting either from scratch purely for LLM routing is usually the wrong call; an LLM-native gateway will be a better fit.

Kong's AI plugin set is genuinely deep: semantic caching and semantic routing, a RAG injector, prompt templates, MCP and A2A gateways, plus a PII sanitizer covering 20 categories across 9 languages and integrations with Azure, AWS, GCP and Lakera guardrails. Its compliance posture is documented and broad — SOC 2 Type 2, GDPR, CCPA, PCI DSS, CSA STAR Level 1, NIST 800-218. For a regulated enterprise that already standardised on Kong, that combination is hard to match.

The price of that is opacity, and it is significant. Kong publishes no pricing for the AI Gateway: Plus is quoted per gateway per month with no published amount, and Enterprise is custom. Worse for evaluation purposes, Plus caps the AI Gateway at five unique LLM models, which pushes any real multi-model deployment to an Enterprise conversation. Third-party reviews also report the free OSS build lacks semantic caching, analytics and compliance features — so the open-source Kong you can try is not the Kong being described.

APISIX is the opposite trade. The entire project is Apache-2.0 with no paid tier, no gated features and no vendor account required, and it publishes the fastest data-plane numbers here at roughly 18,000 QPS per core at under 0.2 ms added latency. But the AI plugins are thin: no response or semantic caching, no budgets, no virtual keys, no prompt management, and only about ten documented provider integrations against 20-140 for LLM-native gateways. It also has no compliance certifications, support SLA or hosted control plane from the project itself, because it is a foundation project rather than a vendor.

One caution that applies to both, and to this whole category: Kong's headline performance advantage comes from a Kong-run benchmark against mock LLMs, and a third-party guide reports that independent tests show far smaller gaps. APISIX's published numbers are for generic proxying, not LLM paths. Neither figure tells you what your traffic will do.

Which one, concretely

Choose Kong AI Gateway if

  • You already run Kong for API management and want one gateway for everything
  • You need semantic caching, semantic routing, RAG injection or prompt templates
  • You need documented SOC 2 Type 2, PCI DSS, CSA STAR or NIST 800-218 posture
  • You need PII sanitization across many categories and languages

Choose Apache APISIX AI Gateway if

  • You already run APISIX and want basic multi-provider LLM proxying
  • You want a genuinely free, fully Apache-2.0 stack with no gated features
  • You need very high throughput per core and minimal added latency
  • You need mature routing primitives — consistent-hash, health checks, retries with time windows

What catches people out

Side by side

6 of 19 fields differ, marked with a dot. Every figure links to the vendor page it came from. Blank values read Not published rather than No — silence from a vendor is not a negative answer.

Field Kong AI Gateway Apache APISIX AI Gateway
Ease of leaving Derived score, higher is easier 100/100 Easy to leave 100/100 Easy to leave
What kind of product Category Managed gateway Open source
Who runs it Deployment model Managed or self-host Self-host only
Licence Licence Open core Apache-2.0
Model providers reachable Upstream providers 17 10–20
Markup on model prices Token markup Not published None
Fee to add funds Credit purchase fee Not published None
Monthly cost per person Seat fee Not published None
GitHub stars GitHub stars 44,100 16,800
Delay it adds Proxy overhead 12 ms 0.2 ms
Requests per second ceiling Throughput 8,200 rps 18,000 rps
SOC 2 audited SOC 2 audited Yes Not published
Similar-question caching Semantic cache Yes Not published
Content guardrails Content guardrails Yes Yes
Strips personal data PII redaction Yes Not published
Rule-based routing Conditional routing Yes Yes
Prompt versioning Prompt management Yes Not published
MCP support MCP support Yes Yes
Usage dashboards and logs Observability Yes Yes
Settings can live in version control Declarative config-as-code Yes Yes

Verified 3 days ago for Kong AI Gateway and Verified 3 days ago for Apache APISIX AI Gateway. Want more fields, or a third option in the mix? Open these two in the full comparison tool.

Common questions

How much does Kong AI Gateway cost?

Kong publishes no pricing for it. The Plus tier is quoted per gateway per month with no published amount and Enterprise is custom. Plus also caps the AI Gateway at five unique LLM models, so any real multi-model deployment requires an Enterprise conversation.

Is Apache APISIX good enough as an AI gateway?

For basic multi-provider proxying, retries and token-based rate limiting on an existing APISIX deployment, yes. But its AI plugins have no response or semantic caching, no budgets, no virtual keys and no prompt management, and only about ten provider integrations are documented — so it is not a substitute for an LLM-native gateway.

Should I adopt either one just for LLM traffic?

Usually not. Both are mature API gateways that grew AI plugins, and their value comes from already running them for your regular API traffic. If you are starting fresh and only need LLM routing, an LLM-native gateway such as LiteLLM, Portkey or Bifrost will fit better.