Vendor agnostic AI gateway options in 2026

The number of LLM providers keeps growing. OpenAI, Anthropic, Google, Mistral, DeepSeek, Meta, Cohere, and more. Each has different APIs, different pricing, different rate limits, and different strengths.

If you are building anything serious with LLMs, you are probably already using multiple providers. Or you will be soon. The question is not whether to use an AI gateway. It is which one.

This is a practical rundown of the vendor agnostic AI gateway options available in 2026, what they actually do, and how to think about which one fits your setup.

What an AI gateway actually does

Before comparing options, let us be clear about what we are talking about. A vendor agnostic AI gateway sits between your application and LLM providers. It gives you:

• A single API that works with any provider. You write your code once and route to any model.
• Failover and retry logic so a provider outage does not take down your app.
• Cost tracking and budgets so you know what you are spending and can set limits.
• Observability so you can see latency, error rates, and usage patterns.
• Access control so different teams or users can only use approved models.

The value proposition is simple: you should not have to rebuild this infrastructure yourself for every project.

The options

Requesty

Requesty is a fully managed AI gateway with 400+ models across 30+ providers. It is OpenAI compatible, so you change one URL and your existing code works.

What stands out:

• One API key for every provider. No need to create accounts with OpenAI, Anthropic, Google individually.
• Smart routing by cost and latency. Not just round robin, but actual intelligent model selection.
• Built in observability with per token cost tracking, TTFT metrics, and session reconstruction.
• EU hosting option in Frankfurt for GDPR compliance.
• Enterprise governance with 5 layer policy hierarchy, RBAC, budget caps, and PII masking.
• Sub 50ms overhead. You barely notice it is there.

Best for: Teams that want everything managed, from routing to billing to observability. Especially strong for teams that do not want to manage provider accounts individually.

Pricing: Pay as you go, per token. $10 free credits to start. No minimums.

LiteLLM

LiteLLM is the most popular open source LLM proxy. It is Python based and supports 100+ models with an OpenAI compatible API.

What stands out:

• Open source and self hosted. Full control over your infrastructure and data.
• Good model coverage with a large community maintaining provider adapters.
• Virtual keys and basic budget controls.
• Active development with frequent releases.

Trade offs:

• You host it yourself. That means Postgres, Redis, load balancers, monitoring, security patches, scaling.
• BYOK only. You need your own API keys for every provider.
• Observability is basic compared to managed options. You will probably add Grafana or a third party tool.
• No SLA. If it goes down at 3am, that is your problem.

Best for: Teams with strong DevOps capacity that want full control and are comfortable self hosting.

OpenRouter

OpenRouter is a managed gateway focused on model access and pricing transparency.

What stands out:

• Large model catalog with competitive pricing.
• Simple API that is easy to get started with.
• Good for individual developers and small teams.

Trade offs:

• Limited enterprise governance features. No RBAC, no team budgets, no PII masking.
• Less focus on observability. Basic usage stats but not deep analytics.
• No EU hosting option for data residency requirements.

Best for: Individual developers and small teams that want easy access to multiple models with simple pricing.

Portkey

Portkey offers a gateway with strong observability and prompt management features.

What stands out:

• Good logging and trace features.
• Prompt management and versioning.
• Virtual keys for provider abstraction.

Trade offs:

• Open source version requires self hosting with Docker, Redis, and Postgres.
• Managed plans start at $49/month with log limits.
• Enterprise features require sales engagement.

Best for: Teams that prioritize prompt management and logging alongside routing.

Kong AI Gateway

Kong AI Gateway adds AI capabilities to Kong's enterprise API gateway.

What stands out:

• If you already run Kong, adding AI routing is incremental.
• Strong API management, rate limiting, and authentication.
• Enterprise RBAC and compliance features.

Trade offs:

• It is a general purpose API gateway with AI bolted on. Not built specifically for LLM workloads.
• Requires Kubernetes and significant platform engineering.
• Enterprise license required. No free tier.
• AI specific features (cost tracking, smart routing, prompt caching) are limited compared to purpose built gateways.

Best for: Organizations that already use Kong for API management and want to consolidate.

Cloudflare AI Gateway

Cloudflare AI Gateway leverages Cloudflare's edge network for AI request proxying and caching.

What stands out:

• Response caching on Cloudflare's edge network for fast repeated queries.
• Basic rate limiting and request logging.
• Free tier available.

Trade offs:

• It is a proxy, not a smart router. No cost or latency aware model selection.
• BYOK only. You need your own provider API keys.
• Limited observability. Request counts and basic analytics, not per token cost tracking.
• No enterprise governance, team budgets, or PII masking.

Best for: Teams already on Cloudflare that want basic caching and proxying for AI requests.

How to choose

The decision comes down to three questions:

1. Do you want to self host or use a managed service?

If you want to self host: LiteLLM is the clear leader in open source. You get full control, but you own the infrastructure.

If you want managed: Requesty, OpenRouter, and Portkey (managed plan) are your options. Requesty is the most complete for teams that need governance, observability, and smart routing.

2. How much infrastructure complexity can you absorb?

If you have a platform team that manages Kubernetes: Kong AI Gateway or LiteLLM can work, but expect weeks of setup and ongoing maintenance.

If you want to ship this week: Requesty or OpenRouter. Change one URL and you are live.

3. What are your compliance requirements?

If you need EU data residency, SOC2, GDPR, or HIPAA: Requesty has these built in. Kong has enterprise compliance but requires self managed infrastructure. Most other options do not offer specific data residency guarantees.

The bottom line

The AI gateway space has matured significantly. In 2026, there is no excuse for calling LLM providers directly without a gateway layer. The question is just which one.

If you are starting fresh, a managed gateway saves you months of infrastructure work. If you already have the DevOps muscle, open source gives you control. Either way, the core capability is the same: one API, many models, automatic failover, cost visibility.

We built Requesty because we believe the gateway should disappear into the background. You should not think about it. You set your policies, point your code at the gateway, and focus on building your product. The routing, failover, caching, and cost optimization just happen.

Get started for free with $10 in credits.