Best AI gateway

Combined ranking

1. 1
   LiteLLMGrade ↗Visit ↗—19 pts

   GPT #2Claude #1Gemini #1Grok #1

   The de facto open-source standard — a single OpenAI-compatible endpoint fronting 100+ providers with load balancing, fallbacks, retries, per-key/per-team budgets and rate limits, and native hooks into Langfuse/OTel/Prometheus for observability; self-hostable so no data leaves your VPC, and its virtual-key + spend-tracking model fits the typical platform team standing up an internal gateway.

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   Claude The de facto open-source standard — a single OpenAI-compatible endpoint fronting 100+ providers with load balancing, fallbacks, retries, per-key/per-team budgets and rate limits, and native hooks into Langfuse/OTel/Prometheus for observability; self-hostable so no data leaves your VPC, and its virtual-key + spend-tracking model fits the typical platform team standing up an internal gateway.

   Gemini Unmatched provider coverage standardizing 100+ LLM backends to the OpenAI specification, excellent virtual key management with granular per-user budget tracking and TPM/RPM rate limiting, and seamless metric/log export to Prometheus, OpenTelemetry, and external observability tools.

   Grok Broadest practical multi-provider coverage (100+/140+), mature virtual-key system with hard RPM/TPM budgets and spend caps that actually reject over-limit traffic, reliable fallbacks/load-balancing, OpenAI-compatible proxy plus OTEL/Prometheus observability and admin spend tracking; free MIT self-host delivers the highest real-world control and cost efficiency for typical production practitioners who can run a Docker/K8s service (near-tie with pure edge options only on zero-ops axis)

   GPT Near-tie with Portkey for engineering-heavy teams; arguably the best self-hosted choice because it gives a broad provider abstraction plus routing, authentication, virtual-key-style controls, spend tracking, logging hooks and rate limiting while keeping the gateway under your control. ([LiteLLM][3])

   Where it falls short

   per GPT Its operational and observability experience is less cohesive out of the box than Portkey's polished gateway-plus-observability control plane, so teams inherit more infrastructure and configuration responsibility.

   per Claude The Python proxy is operationally fiddly at scale (latency overhead, config sprawl, Postgres/Redis dependencies) and its self-serve support burden falls on you — not for teams wanting a hands-off managed SLA.

   per Gemini Python/FastAPI foundation introduces higher memory overhead and per-request latency compared to compiled gateways, making it less ideal for ultra-high-throughput, sub-millisecond edge requirements without horizontal scaling.

   per Grok Python runtime adds measurable overhead and ops burden at sustained high RPS without the newer Rust path or external Redis/Postgres tuning

2. 2
   PortkeyGrade ↗Visit ↗—13 pts

   GPT #1Claude #2Gemini #2Grok —

   Best overall balance of production routing, retries/fallbacks, load balancing, conditional routing, caching, request/token rate limits, budgets, guardrails and unusually deep built-in OpenTelemetry-compatible observability; managed and self-hosted options make it the strongest default for teams wanting one AI control plane. ([Portkey][1])

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   GPT Best overall balance of production routing, retries/fallbacks, load balancing, conditional routing, caching, request/token rate limits, budgets, guardrails and unusually deep built-in OpenTelemetry-compatible observability; managed and self-hosted options make it the strongest default for teams wanting one AI control plane. ([Portkey][1])

   Claude The most complete managed gateway for the routing+limits+observability triad — low-latency edge gateway with conditional routing, fallbacks, semantic + simple caching, granular rate/budget limits, plus first-class tracing, logs, and guardrails in one console; strong choice for teams that want production governance without building it.

   Gemini Near-tie with LiteLLM; delivers ultra-low-latency routing, sophisticated multi-model fallback, load-balancing, and canary deployments, paired with robust out-of-the-box tracing and request analytics.

   Where it falls short

   per GPT Its best fine-grained governance and rate-limit capabilities are concentrated in paid/enterprise tiers, so cost-conscious teams willing to operate infrastructure themselves may get better value elsewhere. ([Portkey][2])

   per Claude Commercial SaaS with per-request pricing and a data-plane-in-the-loop model; full observability value pushes you toward their cloud, so the fully air-gapped, cost-free path is weaker than LiteLLM's.

   per Gemini Advanced governance, guardrails, and centralized UI features heavily push users toward its managed cloud control plane rather than fully self-contained open-source deployments.

3. 3
   Cloudflare AI GatewayGrade ↗Visit ↗incumbent—10 pts

   GPT #4Claude #3Gemini #5Grok #2

   Zero-ops edge rate limiting, response caching, analytics and basic multi-provider proxying with free core tier and no markup on provider spend; lowest friction observability and spend visibility for any practitioner already on (or willing to use) Cloudflare, delivering immediate value without infra or per-request fees

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   Grok Zero-ops edge rate limiting, response caching, analytics and basic multi-provider proxying with free core tier and no markup on provider spend; lowest friction observability and spend visibility for any practitioner already on (or willing to use) Cloudflare, delivering immediate value without infra or per-request fees

   Claude Runs at Cloudflare's edge with near-zero added latency, unified analytics/logging, caching, and rate limiting across providers, all with essentially no infra to operate — excellent value for teams already on Cloudflare wanting instant observability and throttling.

   GPT Excellent value and exceptionally low-ops deployment, with analytics/logging, caching, fixed or sliding rate limiting, retries, fallback and increasingly capable dynamic routing; particularly compelling for applications already on Cloudflare's edge. ([Cloudflare Docs][5])

   Gemini Massive global edge distribution with zero-maintenance setup, offering instant response caching, fundamental rate limiting, and basic request analytics at minimal cost.

   Where it falls short

   per GPT Less flexible as a self-controlled, provider-neutral AI infrastructure layer than LiteLLM, Portkey or Kong because it is fundamentally tied to Cloudflare's managed platform.

   per Claude Routing/fallback logic and fine-grained per-team budgeting are thinner than LiteLLM/Portkey; it's a caching+visibility+limit layer more than a full policy-driven router.

   per Gemini Lacks deep LLM-specific observability (such as span-level tracing or evaluation metadata) and offers limited multi-provider payload transformation capabilities.

   per Grok Shallow conditional/policy routing and multi-tenant controls; ecosystem lock-in and limited depth for complex internal governance or non-Cloudflare stacks

4. 4
   Kong AI GatewayGrade ↗Visit ↗incumbent—7 pts

   GPT #3Claude #4Gemini #4Grok —

   Strongest choice when AI traffic must be governed like serious enterprise API traffic: mature routing infrastructure, sophisticated distributed rate limiting, AI-specific rate-limit controls, authentication, policy plugins and OpenTelemetry/analytics capabilities extend beyond simple LLM proxying into MCP and A2A governance. ([Kong Docs][4])

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   GPT Strongest choice when AI traffic must be governed like serious enterprise API traffic: mature routing infrastructure, sophisticated distributed rate limiting, AI-specific rate-limit controls, authentication, policy plugins and OpenTelemetry/analytics capabilities extend beyond simple LLM proxying into MCP and A2A governance. ([Kong Docs][4])

   Claude Extends a battle-tested API gateway (Kong/Konnect) with AI-specific plugins for multi-LLM routing, token-based rate limiting, prompt governance, and metrics — the strongest fit for enterprises that need AI traffic governed by the same platform, RBAC, and Ops tooling as the rest of their APIs.

   Gemini Industry-standard enterprise API gateway performance and reliability, providing sub-millisecond overhead, unified security/auth policies, global rate limiting, and centralized governance across both traditional APIs and LLM workloads.

   Where it falls short

   per GPT Considerably heavier than AI-native gateways for a team that only needs model routing, quotas and LLM telemetry; its advantage is greatest when Kong is already part of the platform architecture.

   per Claude Heavier to deploy and reason about, and its observability is infrastructure-flavored (metrics/logs) rather than LLM-native trace/eval tooling — overkill for a small team just wanting a proxy.

   per Gemini High configuration complexity and steep operational overhead; heavyweight and over-engineered for small teams wanting a simple, dedicated AI proxy.

5. 5
   HeliconeGrade ↗Visit ↗—5 pts

   GPT #5Claude #5Gemini #3Grok —

   Best-in-class developer-centric observability and prompt analytics with instant one-line integration, comprehensive cost and latency tracking, smart caching, and flexible user-level rate limiting.

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   Gemini Best-in-class developer-centric observability and prompt analytics with instant one-line integration, comprehensive cost and latency tracking, smart caching, and flexible user-level rate limiting.

   GPT Best observability-first contender: a unified OpenAI-compatible gateway across 100+ providers with automatic provider routing/failover, detailed LLM monitoring and unusually useful per-user/per-property request or cost rate limits; near-tie with Cloudflare if debugging and LLM analytics matter more than infrastructure control. ([Helicone OSS LLM Observability][6])

   Claude Observability-first gateway that's trivial to adopt (one-line proxy/base-URL change), giving rich request logging, cost/latency analytics, caching, and rate limiting; open-source and self-hostable, ideal when visibility is the primary goal and routing needs are modest.

   Where it falls short

   per GPT Gateway traffic-management and enterprise policy depth still trails the more mature control-plane capabilities of Portkey and Kong, making it strongest when observability is the primary requirement.

   per Claude Routing and multi-provider failover are comparatively basic — a monitoring layer that limits, not a sophisticated policy router; teams needing complex conditional routing will outgrow it.

   per Gemini Primarily designed as an observability-and-caching layer rather than a dynamic multi-provider routing engine with complex fallback logic.

6. 6
   Envoy AI GatewayGrade ↗Visit ↗—3 pts

   GPT —Claude —Gemini —Grok #3

   Production-stable 1.0 Kubernetes-native data plane with token-aware/quota rate limiting, cross-provider translation and failover across 16 providers, hostname multi-tenancy, and first-class OpenTelemetry GenAI metrics/traces; strongest infrastructure-grade routing + observability combination for teams already operating Envoy/K8s

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   Grok Production-stable 1.0 Kubernetes-native data plane with token-aware/quota rate limiting, cross-provider translation and failover across 16 providers, hostname multi-tenancy, and first-class OpenTelemetry GenAI metrics/traces; strongest infrastructure-grade routing + observability combination for teams already operating Envoy/K8s

   Where it falls short

   per Grok Requires Kubernetes and Envoy operational expertise; overkill and higher barrier for non-platform practitioners or simple app teams

7. 7
   BifrostGrade ↗Visit ↗—2 pts

   GPT —Claude —Gemini —Grok #4

   Go single-binary self-host with microsecond-class overhead even at multi

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   Grok Go single-binary self-host with microsecond-class overhead even at multi

Just missed the top 5

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Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled on demand