Compare AI gateways: pricing, routing and migration

Find an alternative to your current gateway or compare two products directly. Start with the model you need, the controls your application uses and the total cost of completing a task.

The guides below explain when to choose each product, when to keep your current service, and what to test before moving. Product facts link to official documentation; worked examples state their assumptions.

Buyer guides

  1. Best AI gateways by use case

    Shortlist AI gateways by the work you need done: managed model access, controls for existing provider accounts, request observability or an API platform you already operate. Compare eight options using a concrete workload and cost per accepted task.

  2. OpenRouter alternatives

    Shortlist managed APIs, BYOK gateways, self-hosted proxies or dedicated inference by the problem you need to solve. Includes a practical partial-migration example.

  3. Managed vs self-hosted AI gateways

    A managed AI gateway gives the service operator responsibility for gateway deployment, scaling and much of the incident path. A self-hosted gateway puts infrastructure, credentials, storage, upgrades and availability in your team's hands. Managed access is usually the shorter path to production. Self-hosting is justified when infrastructure location, custom policy or provider-account control is worth the ongoing operations.

  4. AI gateway vs direct provider APIs

    Direct provider APIs give the shortest path to provider-native features, contracts and support. An AI gateway earns its extra hop when several applications need shared credentials, model access, routing, spend policy or request evidence. Use direct integration for one stable provider or unique native capability. Use a gateway when duplicated integration and governance work has become a real operating cost.

Product comparisons

  1. KeepRouter vs OpenRouter

    KeepRouter is a managed, prepaid model catalog with public customer prices, OpenAI- and Anthropic-compatible routes for supported chat models, and private operator-managed upstream routing. OpenRouter is a multi-provider API whose current documentation exposes request-level provider selection, sorting, fallback, data-policy, and BYOK controls. Choose KeepRouter for a bounded catalog and a simpler purchasing path; choose OpenRouter when your application must control provider routing directly.

  2. KeepRouter vs Portkey

    KeepRouter sells managed access to models in its public catalog through prepaid credit and KeepRouter keys. Portkey's current documentation says its former Virtual Keys flow has migrated to Model Catalog, where teams add provider credentials and manage organization-level budgets, rate limits, model allowlists, and access. KeepRouter fits teams that want the model purchasing layer managed; Portkey fits teams that want to govern provider relationships they control.

  3. KeepRouter vs LiteLLM

    KeepRouter is a hosted model-access service with a bounded public catalog, prepaid customer billing, and no proxy infrastructure for customers to operate. LiteLLM is software available as a Python SDK or Proxy Server; its official docs describe provider translation, retry and fallback routing, virtual keys, budgets, logging, cost tracking, and rate limiting. Choose KeepRouter to buy a managed path; choose LiteLLM when owning the gateway and provider configuration is the requirement.

  4. KeepRouter vs Cloudflare AI Gateway

    Compare managed model access with Cloudflare traffic controls, including Unified Billing fees, current endpoints and the caching behavior a migration must preserve.

  5. KeepRouter vs Together AI

    KeepRouter is a managed, prepaid catalog for supported models from several makers, with published customer routes and prices. Together AI focuses on serving open-weight models through serverless and dedicated inference, and also offers a training path. Choose by required model, deployment control, billing account and workload, then test the exact route rather than assuming the shared OpenAI client shape makes responses equivalent.

  6. KeepRouter vs Fireworks AI

    KeepRouter offers prepaid access to the exact models and routes in its public catalog. Fireworks AI offers open-model inference through serverless and on-demand deployments, with training and serving controls beyond a gateway catalog. If you need a specific deployment shape or tuned model, test Fireworks directly; if you need listed multi-maker routes under one managed account, evaluate KeepRouter against the same application workload.

  7. KeepRouter vs Vercel AI Gateway

    Compare KeepRouter and Vercel AI Gateway by supported models, provider options, BYOK budget behavior and concrete migration work, including AI SDK applications.

  8. KeepRouter vs Helicone

    Choose KeepRouter when the main requirement is managed model access through a focused API and catalog. Choose Helicone when routing must sit beside detailed request observability, cost tracking, sessions, prompt operations, caching, and custom rate limits. Helicone now has a managed AI Gateway as well as its open-source observability platform, so it should not be described as only a logging proxy.

  9. KeepRouter vs Kong AI Gateway

    Choose KeepRouter when you want a hosted model-access service without operating an enterprise gateway or arranging each upstream provider integration. Choose Kong AI Gateway when your organization already runs Kong or needs self-hosted or hybrid deployment, centralized credentials, traffic policies, AI plugins, and governance for model, MCP, or A2A traffic. The products occupy different layers.

  10. KeepRouter vs Amazon Bedrock

    Choose KeepRouter when you want a managed model catalog, one KeepRouter account, and a smaller integration surface. Choose Amazon Bedrock when AWS IAM, regional deployment, model and agent services, and AWS-native governance are part of the requirement. Bedrock now documents several inference API patterns, including Responses, Messages, Chat Completions, Converse, and Invoke, but support still varies by model and endpoint.

  11. KeepRouter vs Gemini Enterprise Agent Platform

    KeepRouter is the narrower choice for managed model access through a public catalog and KeepRouter credentials. Gemini Enterprise Agent Platform is the current Google Cloud product name for the platform that now includes former Vertex AI capabilities, Model Garden, Agent Studio, Agent Runtime, evaluation, tuning, and cloud governance. Existing Vertex AI users should check the current resource and SDK documentation before migrating.

  12. KeepRouter vs Microsoft Foundry

    KeepRouter fits teams that want a managed model API with KeepRouter credentials and a bounded public catalog. Microsoft Foundry, formerly Azure AI Foundry, is an Azure platform for models, agents, tools, projects, evaluation, tracing, monitoring, and enterprise policy. Foundry has several endpoint families, so an OpenAI SDK example should not be read as one universal endpoint for every workload.

  13. KeepRouter vs Hugging Face Inference Providers

    KeepRouter is a focused managed model API with its own public catalog, routes, credentials, and prepaid ledger. Hugging Face Inference Providers is a proxy integrated with the Hub, one HF token, provider selection policies, centralized billing or custom provider keys, and APIs for several inference tasks. Its OpenAI-compatible endpoint is documented for chat, while broader tasks use Hugging Face clients or task-specific HTTP calls.

  14. Vercel AI Gateway vs OpenRouter

    Compare provider restrictions, fallback, BYOK budgets and SDK migration. Both offer configurable routing; choose with the exact policies and task costs your app needs.

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