Higress vs Apache APISIX AI Gateway
The question that decides it: Is the deciding factor the depth of the AI plugin shelf, or request-path reliability and framework integrations that work without you assembling them?
Our verdict
If you need provider breadth, exact and semantic caching, per-consumer token quotas and PII masking from the gateway itself, and you are willing to audit plugin defaults before trusting them, Higress. If you need dependable request-path behaviour — active health checks, unhealthy-node ejection, ordered and weighted provider fallback, a documented request timeout — and documented LangChain, LangGraph, LlamaIndex and Vercel AI SDK paths, Apache APISIX.
Why
These two are unusually well matched: both Apache-2.0, both foundation-governed, both general-purpose API gateways that grew an AI plugin layer, both BYOK-only with no token markup and no meter. Governance differs in degree rather than kind — APISIX is an Apache Software Foundation top-level project on a regular release train through 3.16 to 3.18 between April and August 2026, while Higress came out of Alibaba Group and entered the CNCF Sandbox on 15 March 2026 with Alibaba, Ant Group, BOSS Zhipin, Cathay Insurance, Ctrip, DJI, Kuaishou, Sealos and Vipshop named as adopters. The engine underneath is the real structural difference. Higress is a compiled stack: an Envoy data plane and a Go control plane built on Istio, extended with Wasm plugins written in Go, Rust or JavaScript with sandbox isolation and hot updates. APISIX is an interpreted OpenResty proxy, 81.6% Lua, where Java, Go, Python and Node plugins run out of process over RPC and Wasm is still experimental. APISIX carries 16,800 stars against Higress's 9,273.
On coverage it is not close. Higress's ai-proxy enumerates 31 named provider types on its Chinese reference page, from OpenAI and Azure through Qwen, DeepSeek, Bedrock, Vertex, Triton and DeepL, and claims 100+ models on three separate vendor pages. APISIX's ai-proxy reference enumerates ten provider values — openai, deepseek, azure-openai, aimlapi, anthropic, openrouter, gemini, vertex-ai, bedrock and openai-compatible — plus "other OpenAI-compatible APIs", against a "20+ model providers" claim on its AI gateway page. Both auto-detect the Anthropic Messages format from a /v1/messages path and convert it, both do embeddings, and neither documents audio, image generation or batch endpoints at all. Higress additionally offers a protocol: original mode that forwards a provider's native wire format untouched, which is the escape hatch APISIX answers with override.endpoint and its openai-compatible provider type.
The plugin shelves then diverge along a clean line: Higress is deeper on AI features, APISIX is more dependable in the request path. Higress ships exact-match and semantic caching in one ai-cache plugin, per-consumer token quotas held in Redis by ai-quota, consumer credentials verified against an x-api-key header, ai-data-masking for regex-based PII replacement, ai-security-guard for inline moderation, ai-statistics reporting tokens across gateway, route, service and model dimensions, and a 41-plugin marketplace whose other entries are ordinary gateway concerns. APISIX has no gateway-owned cache documented anywhere, and no dollar budgets or prompt management. What it does have is the reliability layer Higress is missing: ordered fallback through provider.priority with weighted distribution through provider.weight, round-robin or consistent-hash balancing, active upstream health checks with automatic ejection of unhealthy nodes, and an ai-proxy timeout key defaulting to 30,000 ms within a 1 to 60,000 ms range. Higress's equivalents are shallower and mostly off: retryOnFailure is disabled by default with maxRetries 1, no documented backoff, and retries only on non-streaming requests; failover is disabled by default and health-checks only individual API keys rather than upstreams, with no circuit breaker; model fallback is a console-only setting with a single target rather than an ordered chain; and ai-proxy's 120,000 ms timeout applies to context retrieval, not to the model call, leaving the Ingress annotation you actually want defaulting to no timeout at all.
Neither project can sell you anything, and that shows up identically in the compliance columns with a small difference in candour: APISIX records SOC 2, ISO 27001, GDPR DPA, HIPAA BAA and FedRAMP as not applicable, while Higress records the same fields as not published with an explanation that certification would attach to your own deployment. Same practical answer, and in both cases the absence is a property of foundation software rather than a gap someone forgot to fill. Where they genuinely differ is the commercial adjacency and how transparently it is priced. APISIX's steward API7 publishes a rate card — Cloud Standard at $2 per 1M API calls plus $250 per gateway group per month and $10 per service per month, Enterprise licensed annually by gateway CPU core — and also supplies much of the framework documentation, covering LangChain and LangGraph, LlamaIndex, the OpenAI and Anthropic SDKs and a Vercel AI SDK path. Higress documents no framework integration at all: neither LangChain nor LlamaIndex appears in its documentation index or plugin marketplace, and its managed path is Alibaba Cloud AI Gateway, where Serverless Standard "starts at ¥0 and charges only for actual usage" and the Feitian Exclusive Edition is negotiated. That same Alibaba comparison page marks automatic fault detection and recovery as unsupported and multi-AZ deployment, rate-limit degradation, monitoring and alerting, and enterprise observability as build-it-yourself for the open-source edition, which is a useful statement of where the free version is expected to stop.
Which one, concretely
Choose Higress if
- You need broad provider coverage now — 31 documented provider types against ten
- You want exact-match and semantic caching, per-consumer token quotas and PII masking from the gateway
- You want to replace ingress-nginx: Higress is annotation-compatible and covers ingress, microservices and LLM traffic in one binary
- You want plugins compiled to Wasm in Go, Rust or JavaScript rather than Lua in the request path
Choose Apache APISIX AI Gateway if
- You need reliability primitives that work as documented: health checks, node ejection, priority and weighted fallback, a real default timeout
- You want documented LangChain, LangGraph, LlamaIndex and Vercel AI SDK integration paths
- You want a governance model where no single company can steer the project, and a published rate card if you later want support
- You already run APISIX and etcd, and adding AI routing should not mean adding a second gateway
What catches people out
- Higress ships guardrails that inspect nothing until you edit them: ai-security-guard defaults checkRequest and checkResponse to false, denyCode defaults to 200 in both ai-security-guard and ai-data-masking so blocked traffic returns HTTP 200, and the qwen3guard plugin is explicitly fail-open, with the vendor stating that forced fail-close "cannot be described as satisfied" in the current version.
- Higress's English documentation lags its Chinese documentation — 26 provider sections against 31, omitting GitHub Models, Cohere and Dify — and Redis is a hard dependency for caching, token rate limiting, quotas and MCP hosting, with ai-cache's cacheTTL defaulting to 0, meaning never expire.
- APISIX has no response or semantic cache in its AI plugins at all, and ai-rate-limiting's default local policy keeps counters per node, so the effective quota scales with your node count.
- Both sets of published performance numbers describe general gateway traffic, not LLM paths. APISIX's 0.2 ms average and 18,000 QPS per core, or 140,000 QPS on an eight-core AWS server, are not AI-plugin measurements; Higress publishes no per-request overhead figure at all, only a 50% time-to-first-token reduction attributed to LLM-aware load balancing and an aggregate "hundreds of thousands of requests per second" of Alibaba production traffic.
Side by side
Interpret these fields: How much does an LLM gateway lock you in? · LLM gateway compliance: SOC 2, HIPAA and evidence · How LLM gateway failover actually works
3 of 17 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 | Higress | 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 | Open source | Open source |
| Who runs it Deployment model | Managed or self-host | Self-host only |
| Licence Licence | Apache-2.0 | Apache-2.0 |
| Models available Models available | ~100 | Not published |
| Model providers reachable Upstream providers | 26–31 | 10–20 |
| Markup on model prices Token markup | None | None |
| Fee to add funds Credit purchase fee | Not published | None |
| Monthly cost per person Seat fee | Not published | None |
| GitHub stars GitHub stars | 9,458 | 17,155 |
| Delay it adds Proxy overhead | Not published | 0.2 ms |
| Requests per second ceiling Throughput | Not published | 18,000 rps |
| Similar-question caching Semantic cache | Yes | Not published |
| Response caching Response caching | Yes | Not published |
| Separate keys per team or app Virtual keys | Yes | Not published |
| Spending limits Budget controls | Yes | Not published |
| Strips personal data PII redaction | Yes | Not published |
| Content guardrails Content guardrails | Yes | Yes |
for Higress and 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
Which one supports more LLM providers?
Higress, by roughly three to one on documented integrations. Its Chinese ai-proxy reference enumerates 31 provider types and its English one 26, and it claims 100+ models without publishing an enumerated list. APISIX's ai-proxy reference enumerates ten provider values plus other OpenAI-compatible APIs, while its AI gateway page claims 20+ providers. Neither publishes a verifiable model catalogue endpoint.
Does either one have semantic caching?
Higress does, through the same ai-cache plugin that handles exact-match caching: point it at an embedding service and a vector database, with Redis required either way. APISIX does not — no gateway-owned response cache or provider-cache passthrough is documented in its AI plugins, though usage fields such as cached_tokens are surfaced. If caching is the requirement, this pair resolves to Higress immediately.
Can I get an SLA or a SOC 2 report for either?
Not from either project. APISIX records SOC 2, ISO 27001, GDPR DPA, HIPAA and FedRAMP as not applicable and Higress records them as not published; both are self-hosted software where compliance attaches to your own deployment. Commercial support exists next to each: API7 for APISIX with a published rate card, and Alibaba Cloud AI Gateway for Higress, whose Feitian Exclusive Edition offers a negotiable SLA.