Azure API Management

Assuming you mean gateways for LLM APIs—one endpoint for accessing models, routing requests, and controlling usage—these are the established products I’d shortlist. There isn’t a credible universal ranking by customer count, so these are best-by-use-case recommendations, not a market-share ranking.

My practical pick: start with OpenRouter if you want to ship or experiment quickly; LiteLLM if you need to own the infrastructure; Portkey for a multi-team production control plane; or Cloudflare/Vercel if your app already lives in that ecosystem. If choosing LiteLLM, review its security advisories and avoid the compromised PyPI versions 1.82.7 and 1.82.8. (github.com)

These are the AI (LLM) gateways that come up most often. A gateway is a single endpoint in front of many model providers. It adds routing, fallbacks, cost tracking and access control.

Most widely used

• LiteLLM is the open-source, self-hosted default. One source lists it as having the widest adoption, with 53.8K GitHub stars, 100+ providers, and a Python-first design. It's best when you want control and are willing to run it yourself. The same source advises you to pin and verify releases.
• OpenRouter is a managed service with nothing to run. It's recommended for a large model catalog behind a single OpenAI-compatible endpoint. It also suits smaller teams, since it offers breadth and unified billing.
• Portkey is aimed at governance and guardrails. It has an MIT license, 1,600+ models, and is now backed by Palo Alto Networks.
• Cloudflare AI Gateway is managed and runs at the edge. It fits if you already front everything with Cloudflare and want basic caching. Its core features are free.
• Vercel AI Gateway is a managed gateway for teams building with Vercel, Next.js or the AI SDK. It advertises zero markup on tokens.
• Kong AI Gateway suits teams that already run Kong. It's best for enterprises already running a Kong API mesh.
• AWS Bedrock and Azure make sense if you're already in those clouds. One comparison says these options make sense only when a gateway needs to sit inside infrastructure you already run.

Newer or more specialized

• Bifrost (by Maxim AI) is an open-source Go gateway that claims about 11 µs of overhead at 5,000 RPS.
• TrueFoundry is a Kubernetes-native AI gateway with governance, RBAC, and budgets.
• Helicone puts logging and analytics first, gateway second.

Quick picks

Several of these "top 5" lists were published by gateway vendors. The Bifrost rankings come from Maxim AI, which makes Bifrost, and the "LLM Gateway" pick comes from that product's own site. Treat their benchmark claims with caution. LiteLLM, OpenRouter, Portkey and the big infrastructure vendors are the safer bets in terms of real-world usage.

If you tell me your stack, scale, and whether you need to self-host, I can narrow this to one or two.

An AI Gateway (or LLM Gateway) acts as a centralized middleware layer sitting between your applications and underlying model providers (OpenAI, Anthropic, Google Gemini, self-hosted vLLM, etc.).

Instead of managing separate API keys, error handlers, and billing logic across multiple SDKs, an AI Gateway standardizes access behind a single API endpoint—adding load balancing, failovers, semantic caching, rate limiting, PII redaction, cost tracking, and security guardrails.

The leading AI gateways, categorized by primary enterprise and developer use cases, include:

1. Open-Source & Developer-Centric Gateways

LiteLLM (Best Open-Source Proxy for Developer Teams)

• Why it's used: LiteLLM is the most widely adopted open-source LLM proxy. It translates requests from over 100+ model providers into a unified, OpenAI-compatible API spec.
• Key Features: Virtual API key management, per-team budget limits, automatic fallback routes, Prometheus telemetry, and light footprint.
• Best for: Self-hosting teams that want maximum model flexibility without vendor lock-in.

Bifrost (Best High-Performance Open-Source Gateway)

• Why it's used: Built in Go, Bifrost is engineered specifically for ultra-low latency, high-concurrency production workloads where proxy overhead must be minimal.
• Key Features: Sub-millisecond latency, adaptive load balancing, deep telemetry, self-hosted deployment (VPC/air-gapped), and enterprise compliance (SOC2/HIPAA ready).
• Best for: Engineering teams scaling high-throughput, mission-critical AI workloads on self-hosted infrastructure.

2. Managed & Enterprise Gateways

Portkey (Best Enterprise Control & Guardrails)

• Why it's used: Portkey is one of the most mature managed AI gateways on the market, focused heavily on reliability, compliance, and enterprise governance.
• Key Features: Granular retry policies, circuit breakers, prompt management, semantic caching, fallback execution across 1,600+ models, and guardrails for content safety.
• Best for: Enterprise platform teams needing strict governance, policy enforcement, and auditability across multiple AI vendors.

Kong AI Gateway (Best for Existing Infrastructure & API Ops)

• Why it's used: Built as an extension to the industry-standard Kong API Gateway, it allows organizations to manage AI traffic right alongside their existing REST/GraphQL infrastructure.
• Key Features: Token-based rate limiting, PII sanitization, prompt injection protection, dynamic request transformation, and deep enterprise security integration.
• Best for: Enterprise Ops and platform teams already running Kong in production.

TrueFoundry (Best for Multi-Cloud & MCP Agent Workloads)

• Why it's used: TrueFoundry provides an enterprise-ready AI gateway that scales into a broader MLOps platform, including support for agentic tool protocols like Model Context Protocol (MCP).
• Key Features: Latency/cost-based routing, RBAC, SSO, virtual keys, and support for hybrid/air-gapped VPC enterprise deployments.
• Best for: Enterprises needing custom VPC control with advanced agent orchestration support.

3. Edge & Cloud Platform Gateways

Cloudflare AI Gateway (Best for Edge Caching & Fast Setup)

• Why it's used: Positioned at Cloudflare’s global edge network, it adds a proxy layer in front of model providers with virtually zero configuration changes.
• Key Features: Global edge response caching, basic rate limiting, fallback routing, and native analytics in the Cloudflare dashboard.
• Best for: Developers already utilizing Cloudflare workers/infrastructure who want fast caching and observability.

Vercel AI Gateway (Best for Web Applications & Vercel Stack)

• Why it's used: Integrated cleanly into Vercel’s ecosystem and the popular Vercel AI SDK.
• Key Features: Zero token markup, model array fallbacks, provider timeouts, and OpenTelemetry integrations.
• Best for: Frontend and full-stack developers building AI-powered web applications on Vercel.

4. Managed Aggregators & Routers

OpenRouter (Best for Instant Access & Prototyping)

• Why it's used: A zero-ops managed API aggregator that provides instant access to 400+ public, proprietary, and open-weight models under a single credit account.
• Key Features: Automatic provider routing based on price/throughput/latency, drop-in OpenAI API replacement, and live fallback options.
• Best for: Startups and devs trying out dozens of different models without managing dozens of separate API subscriptions.

Quick Selection Matrix

The strongest AI gateway products people actually use are LiteLLM, Portkey, Kong AI Gateway, OpenRouter, Cloudflare AI Gateway, Vercel AI Gateway, Helicone, and TrueFoundry. The right choice depends mainly on whether you prioritize self-hosting, model breadth, enterprise governance, or observability.

Practical recommendations

• For most engineering teams: Start with LiteLLM if self-hosting is acceptable; choose Portkey if you want a managed control plane and stronger governance.
• For a quick prototype: Use OpenRouter.
• For an existing enterprise API platform: Choose Kong AI Gateway.
• For a Vercel application: Use Vercel AI Gateway.
• For Cloudflare-based infrastructure: Use Cloudflare AI Gateway.
• For monitoring AI spend and performance: Use Helicone.
• For strict data residency or isolated infrastructure: Evaluate TrueFoundry, Kong, or self-hosted LiteLLM.

The safest shortlist is LiteLLM, Portkey, Kong, and OpenRouter: they recur most consistently across current comparisons, while the rankings themselves should be treated cautiously because many comparison articles are vendor-produced.

“AI gateway” usually means an LLM gateway: a proxy/control plane in front of OpenAI, Anthropic, Gemini, Bedrock, Azure OpenAI, self-hosted models, etc. It handles routing, fallback, caching, rate limits, cost tracking, guardrails, observability, and sometimes MCP/tool access.

There’s no single best one. The most commonly used/recommended products are:

Practical shortlist

• Best default open-source: LiteLLM
• Best commercial AI-native gateway: Portkey
• Best enterprise API-gateway route: Kong AI Gateway
• Best simple hosted/edge option: Cloudflare AI Gateway
• Best observability companion: Helicone
• Best “one API for many models”: OpenRouter
• Best Azure/Google enterprise route: Azure APIM AI Gateway or Apigee AI Gateway

Recommended stacks

• Startup/MVP: OpenRouter or Portkey Cloud + Helicone
• Self-hosted OSS: LiteLLM + Helicone/Langfuse
• Enterprise governance: Kong AI Gateway or Azure APIM/Apigee + Portkey/LiteLLM where needed
• Cloudflare-native: Cloudflare AI Gateway
• Kubernetes-native: Envoy AI Gateway, Apache APISIX, or Higress

If you only want one recommendation: start with LiteLLM if you want self-hosted/open-source; choose Portkey if you want a polished managed AI gateway. If your company already runs Kong or Azure API Management, evaluate those first because procurement, auth, and governance are usually easier.

Note: if by “AI gateway” you mean an MCP gateway for tool/server access, that’s a different category — look at Docker MCP Gateway, Kong MCP Gateway, Solo.io, etc.

AI gateways (also called LLM gateways or proxies) sit between your apps/agents and multiple model providers. They provide a unified OpenAI-compatible API, handle routing/fallbacks across providers (e.g., OpenAI, Anthropic, Groq, Bedrock, self-hosted models), add features like semantic/exact caching, cost tracking/budgets/virtual keys, observability/logging, guardrails/PII redaction, rate limiting, and retries—without changing much code.

They are popular in 2026 for production LLM apps, agents (including MCP/tool calling), and teams managing multi-provider spend or compliance. Adoption shows in GitHub stars (e.g., LiteLLM’s high count), forum discussions, and repeated mentions in comparisons. There is no single “best”—it depends on self-hosting needs, performance, governance, or existing stack (e.g., Cloudflare or Kong).

Here are the top brands/products people actually use, drawn from 2026 comparisons, adoption signals, and real-world feedback:

• LiteLLM — Most widely adopted open-source/self-hosted option (MIT license core; ~53.8K GitHub stars reported). Supports 100+ providers, virtual keys, per-team budgets, fallbacks, caching, and Prometheus metrics. Python-first proxy (self-hosted via Docker/Helm or hosted/enterprise tiers). Best for teams wanting full control and zero markup on their own keys. Trade-offs: Ops overhead at scale (multiple services like Postgres/Redis); some note latency or config sprawl in production. Frequently the default self-hosted pick.

• Portkey (now integrated into Prisma AIRS / Palo Alto Networks) — Strong for enterprise governance, guardrails, routing/fallbacks, semantic caching, observability, and compliance (SSO, RBAC, audits). Self-hosted core (MIT/Apache) + managed/private cloud options; supports 1,600+ models. Good for production safety and prompt management. Trade-offs: Hosted tiers meter logs; enterprise features may require paid plans. Popular for teams prioritizing controls over pure self-hosting.

• OpenRouter — Leading managed aggregator/marketplace for broad, low-friction access (400–500+ models from 60+ providers). One API key, automatic fallbacks/routing (by price/latency/etc.), OpenAI-compatible. No self-hosting needed. Popular for quick prototyping or unified billing. Trade-offs: ~5.5% fee on credit purchases (pass-through inference pricing otherwise); hosted only (data transits their service). Strong for developers wanting zero ops.

• Bifrost (Maxim AI) — High-performance self-hosted Go binary (Apache 2.0). Ultra-low overhead (~11 µs at 5K RPS), strong for high-throughput workloads. Supports multiple providers, load balancing, fallbacks, semantic caching, and MCP/tool traffic. Best for performance-sensitive or high-RPS self-hosted setups. Trade-offs: Fewer providers than LiteLLM in some reports; newer ecosystem. Often praised in benchmarks vs. LiteLLM.

• Kong AI Gateway — Best if you already run Kong for API management. Extends to LLM/MCP/A2A traffic with plugins/policies for routing, limits, caching, and guardrails. Open core + commercial options. Trade-offs: Steeper learning curve if not already in the Kong ecosystem; AI features can feel retrofitted. Solid for platform/API teams.

Other notable mentions (widely discussed for specific use cases):

• Cloudflare AI Gateway: Managed edge proxy with free core features (caching, logging, rate limits). Ideal if already on Cloudflare.
• Vercel AI Gateway: Managed, zero token markup, tight integration with Vercel AI SDK. Good for Vercel/Next.js users.
• Helicone: Observability- and logging-first (cost tracking, traces); self-host or managed. Complements routing gateways.

Quick decision guide (common recommendations):

• Self-hosted control/no markup → LiteLLM or Bifrost.
• Broad models, zero infra → OpenRouter.
• Governance/guardrails/enterprise → Portkey/Prisma AIRS.
• Existing stack (Cloudflare/Kong/Vercel) → Use the native one.
• Observability focus → Helicone (or pair with others).

Many teams start with OpenRouter or LiteLLM for speed, then layer governance or switch for scale/performance. Evaluate based on your volume, compliance needs, data residency, and whether you want to self-host. Check current docs/pricing for the latest (features and acquisitions evolve quickly). Reddit threads and benchmarks often highlight real ops trade-offs like latency or setup effort.

The most widely used and top‑rated AI gateways today are TrueFoundry, Kong AI Gateway, Portkey, LiteLLM, and Lunar.dev, each serving different enterprise and engineering needs.

✅ What an AI Gateway Is (Why It Matters)

An AI gateway is a control layer that sits between your applications and multiple AI/LLM providers, handling routing, security, governance, cost management, and observability through a single API. It’s now a standard component in enterprise AI stacks.

⭐ The Best AI Gateways (Based on Gartner, TrueFoundry, and Braintrust Rankings)

1. TrueFoundry AI Gateway — Most complete enterprise solution

Why it’s widely used: Sub‑5ms latency, deep governance, SOC 2 Type 2 + HIPAA compliance, and full multiprovider routing. Strengths:

Enterprise-grade observability and cost attribution Unified API for OpenAI, Anthropic, Gemini, AWS, Azure, Databricks, Mistral, Groq, Together, and self-hosted models Strong MCP (Model Context Protocol) support Air‑gapped and self-hosted deployment options Best for: Large enterprises managing multiple AI providers and strict compliance needs.

2. Kong AI Gateway — Best for companies already using Kong

Why people use it: Kong is a dominant API gateway; adding AI routing is convenient for existing customers. Strengths:

Mature API security stack (OAuth2, JWT, mTLS, RBAC) Works well when AI is a small extension of an existing API program Trade-offs: Not built for LLM-native workloads; lacks token-level cost attribution, agent observability, and MCP support. Best for: Organizations with Kong already deployed and low-volume AI traffic.

3. Portkey — LLMOps + gateway in one platform

Why it’s popular: Unified API access to 100+ LLMs plus guardrails, prompt management, and governance tools. Strengths:

50+ prebuilt guardrails (PII detection, content filtering) SOC2, ISO27001, HIPAA, GDPR compliance SaaS, hybrid, and air-gapped deployments Trade-offs: Budget limits only in enterprise tier Some users report overwhelming UI and limited export functionality Best for: Teams building complex AI applications needing guardrails + prompt management.

4. LiteLLM — Most popular open-source gateway

Why engineers use it: Simple, Python-based proxy with universal OpenAI-compatible API routing. Strengths:

Supports 100+ LLM providers YAML-based configuration and Docker deployment Great for cost-conscious teams Trade-offs: No enterprise support or SLAs Frequent regressions and instability at scale Limited observability and security controls Best for: Engineering teams wanting open-source flexibility and full control.

5. Lunar.dev — Best for security and governance teams

Why it’s adopted: Unified governance across AI model traffic, MCP tools, and enterprise APIs. Strengths:

Intelligent routing, caching, rate limiting Centralized auditing and SOC2 enterprise compliance Strong VPC and air-gapped deployment options Best for: Security, IT, and platform engineering teams needing strict governance.

📊 Quick Comparison Table

Gateway | Best For | Key Strengths | Deployment | Sources TrueFoundry | Enterprise AI at scale | Sub‑5ms latency, full governance, cost attribution, MCP | Cloud, self-hosted, air-gapped | 2 Kong AI Gateway | Existing Kong users | Mature API security, basic AI routing | Enterprise API gateway | 2 Portkey | LLMOps + gateway | Guardrails, prompt mgmt, compliance | SaaS, hybrid, air-gapped | 1 LiteLLM | Open-source teams | Universal API, flexible config | Self-hosted, Docker | 2 Lunar.dev | Security & governance | Unified control plane, routing, auditing | VPC, cloud, air-gapped | 1 2 Sources2

✅ Additional Gateways Mentioned in Rankings

Braintrust also lists Braintrust Gateway, SUSE AI Universal Proxy, and Cloudflare AI Gateway as notable options, though they are less widely adopted than the top five.

🔍 What People Actually Use (Real Adoption Signals)

Across Gartner Peer Insights, TrueFoundry’s industry analysis, and Braintrust’s rankings:

TrueFoundry shows the strongest enterprise adoption and performance metrics. Kong is common in companies with existing API gateway infrastructure. Portkey is popular among teams building complex AI apps with guardrails. LiteLLM is widely used in engineering teams for open-source flexibility. Lunar.dev is chosen by security and platform teams needing governance.

If you want, I can help you choose the best gateway for your specific stack (cloud provider, compliance needs, traffic volume, and budget).

The top AI/LLM gateways used for software development, production routing, and infrastructure include:

Top Software & Cloud LLM Gateways

LiteLLM: An open-source Python-based gateway with massive provider coverage and flexibility, boasting over 56,000 GitHub stars and support for a wide range of LLM APIs. Bifrost (Maxim AI): Built with Go (Apache 2.0 core), widely recognized for ultra-low latency, high-traffic production routing, failover reliability, and enterprise governance. Cloudflare AI Gateway: Built directly into the Cloudflare Edge network, ideal for teams already on Cloudflare looking for unified infrastructure management, caching, and analytics. Vercel AI Gateway: Tailored for frontend-heavy and Next.js/Vercel teams emphasizing a smooth developer experience and seamless framework integration. OpenRouter: A managed gateway offering a massive catalog of models through a single unified API without requiring self-hosted infrastructure. Portkey: A governance- and guardrails-heavy gateway option focused on compliance, security, and monitoring.

Top Hardware & Edge AI Gateways

If you are looking for physical edge appliances or smart home gateways:

LinknLink HomeClaw / HomeClaw Max $129.90 LinknLink & more Add to list An open AI smart home gateway designed for Home Assistant, OpenClaw, and Hermes local voice/automation agents (priced around $95–$130). Ubiquiti UniFi AI Key $799.00 Loja Oficial Ubiquiti Store & more Add to list An edge AI appliance engineered to enhance UniFi Protect camera and smart detection environments with high-capacity event processing (priced around $800–$1,000). Firefly GS1-N2 AI Gateway Server $1,499.00 Firefly Store Add to list A high-performance 1U edge AI server featuring dual-core architecture and real-time inference support for industrial or security vision (priced around $1,499). Show more

Are you looking for a software LLM proxy/gateway for an application backend, or a physical edge hardware gateway for smart home/video use?

AI gateways act as a single, unified proxy layer in front of multiple large language model (LLM) providers. They handle critical production needs like load balancing, failover, API key management, rate limiting, budget guardrails, and usage logging.

The top AI gateways that developers and enterprises actually use are categorized below by their primary strengths and use cases:

LiteLLM (Best for Python & Fast Prototyping) What it is: An extremely popular, MIT-licensed Python proxy and toolkit that routes traffic to over 100 model providers using a single OpenAI-compatible API format. Why people use it: It is widely considered the fastest way to stand up a local or self-hosted proxy with budget tracking, virtual keys for different teams, and load balancing out of the box. Check out the details on Vercel's Open Source AI Gateways Comparison. Bifrost (Best for High-Performance Enterprise & Platform Teams) What it is: An open-source, highly performant gateway engineered for minimal latency overhead (roughly 1 1 𝜇 𝑠 at 5,000 requests per second). Why people use it: It can be deployed fully air-gapped, on-premises, or inside a private VPC under an Apache 2.0 license, making it a top pick for security-heavy enterprise environments. Cloudflare AI Gateway (Best for Teams Already on Cloudflare) What it is: A managed cloud service that sits on Cloudflare’s edge network. Why people use it: If your infrastructure already touches Cloudflare, it offers dead-simple setup, built-in caching (to instantly save money on repeated prompts), rate limiting, and real-time analytics without managing dedicated proxy servers. OpenRouter (Best for Model Exploration & Prototyping) What it is: A hosted model marketplace and unified API router. Why people use it: It gives you a single API key to access hundreds of different open-source and proprietary models. While less suited for locked-down enterprise data governance, it is unmatched for trying out different LLMs on the fly. Kong AI Gateway (Best for Enterprise API Management) What it is: The AI extension of the ubiquitous Kong API Gateway ecosystem. Why people use it: Large enterprises that already use Kong for traditional microservices can leverage its native AI Proxy plugins to route, secure, and monitor LLM traffic alongside normal backend traffic—including zero-code tracing integration with observability tools like Langfuse. Langfuse

To help narrow down which gateway fits your stack, tell me:

Are you looking for a self-hosted open-source tool or a fully managed cloud service? What infrastructure or languages (e.g., Python, Kubernetes, Cloudflare) is your app built on?