Ranked comparison

AI Gateway: One API for Every LLM

An AI gateway sits between your app and LLM providers. It gives you one endpoint, automatic failover, and cost controls - so a single provider outage doesn't take your product down.

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Free preview, Starter for the Auto lane, Teams for manual GPT, Claude, and Gemini Pro access. Add-on credits kick in after included plan tokens are used.

Start on cheap auto-routed models first, then move up only when your workload truly needs premium manual control.

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Why teams start here first
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Starter
Auto lane only
Curated cheap model pool with no manual premium-model selection.
Teams
Premium when you need it
Manual GPT, Claude, and Gemini Pro access starts here.
Billing
Plan tokens first
Add-on credits only extend usage after included plan tokens are exhausted.
Evaluation criteria
Latency overheadProvider coverageFailover and circuit breakingCost control and budgetingObservability and logging
1
LLMWiseLLMWise

The only gateway where you can test models side-by-side, blend their outputs, or let one model judge another - all as native API calls. Failover triggers within milliseconds when a provider degrades, and the auto-router picks the cheapest model that can handle each query without any configuration.

Compare, Blend, and Judge are first-class API operations, not afterthoughtsZero-latency heuristic routing classifies queries in microsecondsCredit-based pricing with reserve-and-settle billing - no surprise invoices
2
OpenRouterOpenRouter

The largest model marketplace with 300+ models behind one API. Simplest setup for teams that want breadth over depth. Adds a 5% markup on all requests, which adds up at scale.

Broadest model selection - 300+ models from 60+ providersNear-zero integration effort with OpenAI-compatible endpointActive community and transparent pricing per model
3
PortkeyPortkey

The enterprise pick for teams that need guardrails, semantic caching, and SOC 2 compliance. Open-sourced the core gateway in March 2026. Starts at $49/month for the managed platform.

Enterprise-grade guardrails and access controlsSemantic caching reduces redundant API callsNow open-source (Apache 2.0) for self-hosting the core
4
LiteLLMLiteLLM

The best option if you need full control and can self-host. Open-source Python proxy with 100+ provider integrations and zero markup. Requires DevOps resources to run and maintain.

Fully open-source with no per-request fees100+ provider integrations out of the boxMaximum customization for teams with infrastructure engineering capacity
5
HeliconeHelicone

Observability-first gateway built in Rust for raw speed. Best choice if your primary need is logging, cost tracking, and debugging rather than advanced routing logic.

Rust-based proxy with minimal latency overheadDetailed cost and latency analytics per requestOpen-source and free to self-host
6
Cloudflare AI GatewayCloudflare

Good if you are already in the Cloudflare ecosystem. Built-in rate limiting and caching at the edge. Less flexible for custom routing logic compared to purpose-built gateways.

Global edge network for low-latency routing worldwideNative rate limiting and response cachingFree tier available for low-volume usage
Evidence snapshot

AI Gateway: One API for Every LLM scoring method

Ranking evidence from practical criteria teams use for real production traffic.

Criteria
5
evaluation dimensions used
Models ranked
6
candidates evaluated
Top pick
LLMWise
current #1 recommendation
FAQ coverage
5
selection objections addressed
Our recommendation

For most teams shipping AI features, LLMWise is the fastest path to production-grade multi-model routing with automatic failover and cost optimization built in. If you need to self-host, LiteLLM is the best open-source option. If your priority is observability over routing, Helicone is a strong choice.

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Common questions

What is an AI gateway?
An AI gateway is a proxy layer between your application and LLM providers like OpenAI, Anthropic, and Google. It provides a single API endpoint, handles authentication across providers, manages failover when a provider goes down, and gives you cost and latency visibility. Think of it as a load balancer specifically designed for LLM APIs.
How does an AI gateway reduce costs?
Three main levers: (1) smart routing sends simple queries to cheaper models instead of always hitting the expensive flagship, (2) caching avoids redundant API calls for repeated prompts, and (3) failover prevents wasted tokens on requests that fail mid-stream. In practice, teams that route by complexity instead of using a single model for everything tend to save 25-40%.
What is the difference between an AI gateway and an LLM proxy?
An LLM proxy is a thin forwarding layer that translates between API formats. An AI gateway adds intelligence on top: routing decisions, failover logic, cost controls, and observability. LLMWise is a full gateway - it routes, fails over, optimizes costs, and lets you compare or blend outputs across models.
Do I need an AI gateway for production?
If you are calling a single LLM provider and can tolerate downtime when that provider has issues, you can skip a gateway. If you use multiple models, need failover, or want to optimize costs, a gateway pays for itself quickly. Most production AI apps hit the multi-provider stage within months of launch.
Can I bring my own API keys to an AI gateway?
Yes. LLMWise supports BYOK (Bring Your Own Key) - you can use your own OpenAI, Anthropic, or Google API keys while still getting LLMWise's routing, failover, and analytics. When you use BYOK, you pay the provider directly and skip LLMWise credit charges for those requests.

Start on Auto, move up only when you need it

Free preview, Starter for the Auto lane, Teams for manual GPT, Claude, and Gemini Pro access. Add-on credits kick in after included plan tokens are used.

Start on cheap auto-routed models first, then move up only when your workload truly needs premium manual control.

Starter Auto laneTeams premium manual accessPlan tokens + add-ons
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Related pages
LLM Gateway: Route to Any Model from One EndpointLLM Router: Intelligent Model Selection for Every RequestLLM API: One Integration, Every Major ModelLLM Proxy: One Endpoint, Every AI ProviderLLM Orchestration: Build Multi-Model AI PipelinesLLM failover routing without fragile hand-built recovery logic