Best LLM Gateways in 2026

Spro is a unified AI gateway that sits between your application and AI providers. It gives you one OpenAI-compatible endpoint for models from OpenAI, Anthropic, Google, DeepSeek, xAI, Mistral, Moonshot AI, MiniMax, Z.AI, Qwen, Meta Llama and more, and it speaks the Chat Completions, Responses and Anthropic Messages APIs, so most apps migrate by changing a base URL and an API key. Every model is billed at the provider's price with 0% markup on tokens.

Where Spro differs from a plain router is what is built into the gateway itself. When a model is served by more than one provider, Spro fails over between them and skips a provider that has just failed for 60 seconds, and you can send your own fallback chain or pin a provider. Exact-match and semantic caching are opt-in per request, with an x-spro-cache header that tells you whether you got a hit. Input and output guardrails cover sensitive information, content moderation, language filters and adversarial input such as prompt injection, with log, warn, block or redact actions.

OpenRouter started in early 2023 as an LLM marketplace and describes itself as the largest AI gateway. It gives you one OpenAI-compatible API, one key and one bill for 500+ models from 80+ providers, and its About page cites 700T+ tokens a month and 10M+ users. Inference is billed at each provider's list price; OpenRouter's revenue comes from a fee on credit purchases, 5.5% on Standard and 8% on Business, never on individual requests.

By default OpenRouter load-balances across providers, prioritizing price and deprioritizing any provider that had an outage in the last 30 seconds. You can steer it with sort options (price, throughput or latency), pin or exclude providers, set max prices, require ZDR or data-collection policies, and use model variants such as :nitro, :floor and :exacto. If a provider errors, the request falls back to the next one, and errored attempts are not billed for tokens.

Respan (formerly Keywords AI) is an AI router with built-in observability and automated evals, aimed at teams running AI agents and LLM apps in production. Its gateway gives you one OpenAI-compatible API for 1,000+ models across the major providers, and switching models is a one-word change. Respan was founded in 2024, is based in San Francisco and lists a team of 1-10 people.

You set a fallback chain once, at the organization level or per request, and Respan moves to the next model when a provider errors or rate-limits. Failed requests retry automatically, traffic can be load-balanced across providers and models, and exact repeat requests are served from cache with a configurable TTL. Hard spend limits per key, per customer or organization-wide stop requests at the ceiling rather than only alerting, and costs break down by model, request and end customer.

Portkey is an AI gateway that combines routing with observability, guardrails, governance and prompt management. Its core gateway is open source under the MIT license and can be self-hosted, and its docs describe a unified interface to 250+ models; its homepage cites 1,600+ LLMs and 3,000+ GenAI teams. Note that its site now carries a banner saying Portkey is becoming Prisma AIRS AI Gateway from Palo Alto Networks, so check the current positioning before committing.

The gateway covers fallbacks, automatic retries (up to 5 with exponential backoff), weighted load balancing across keys or providers, conditional routing, timeouts, circuit breakers and canary testing. On top sit request logs and traces, budget and rate limits, virtual keys, simple and semantic caching, 40+ pre-built guardrails with partner integrations such as Patronus, Pangea and AWS Bedrock Guardrails, and a hosted prompt-management product.

LiteLLM is an open-source AI gateway and Python SDK that calls 100+ LLM providers in the OpenAI format; its homepage cites 140+ providers and 1,800+ models. You run the proxy yourself on your own Postgres and Redis, in your own cloud or fully air-gapped, and manage virtual keys, budgets and teams on top. The gateway is MIT-licensed and free to self-host, with a paid Enterprise license key on the same image.

Routing is configurable: simple-shuffle (the recommended default), least-busy, latency-based and cost-based strategies, ordered deployments with automatic failover, cooldowns for deployments that return 429, and RPM/TPM limits. Spend is tracked per key, user and team with budgets and budget durations, caching supports Redis, semantic caches, S3, GCS and in-memory backends, and logging connects to Langfuse, OpenTelemetry, Datadog, S3 and many more.

TrueFoundry's AI Gateway is the proxy layer between your applications and LLM providers and MCP servers. Its homepage cites 1,600+ models and its docs 1,000+ LLMs across 35+ platforms, with OpenAI and Anthropic SDK compatibility, and it covers chat, embeddings, responses, images, audio, video, rerank and realtime endpoints. TrueFoundry says it never marks up tokens: you pay only for the gateway.

It is aimed at governance. You get weighted, latency-based and priority routing with automatic fallback, semantic caching, rate limits and cost or token quotas per user, service or endpoint, budget rules, guardrails for PII, prompt injection and moderation, OpenTelemetry traces and request logs, and an MCP gateway that applies OAuth2 and RBAC to tool calls. It can run as SaaS, with logs in your own storage, or in your VPC, on-prem or air-gapped, and it can front self-hosted models served with vLLM, SGLang, KServe or Triton.

Cloudflare AI Gateway is a gateway that sits in front of your AI provider calls on Cloudflare's network, giving you visibility and control over AI apps. It is available on all Cloudflare plans, and its core features, dashboard analytics, caching and rate limiting, are free. It supports 24 provider-native integrations including Workers AI, OpenAI, Anthropic, Google Vertex AI, Amazon Bedrock, Groq and Mistral, an OpenAI-compatible chat completions endpoint, and a Workers binding.

Caching is exact-match: it is off by default, keyed on a hash of the provider, model and full request body, with a TTL from 60 seconds to a month. Rate limiting is configured per gateway with fixed or sliding windows and returns 429 when exceeded. Dynamic routing lets you build versioned routes with conditional, percentage, rate-limit and budget-limit nodes, and guardrails evaluate prompts and responses with Llama Guard and are billed as Workers AI inference.

Vercel AI Gateway gives you one API key for 400+ models, with, in its words, no markup and no platform fee on tokens. It is available on all Vercel plans and works through the AI SDK, the OpenAI Chat Completions and Responses APIs and the Anthropic Messages API, so moving to it is typically a base URL swap. The default provider choice uses recent uptime and latency, and you can control order, filter providers, sort by cost, time to first token or throughput, and set timeouts and fallbacks.

Billing works through credits: every team has a free tier covering a subset of models and a paid tier where you buy credits and pay provider list price, with optional auto top-up. BYOK is paid-tier only with no markup, and failed BYOK requests retry on system credentials that are charged to your credits. Optional add-ons include custom reporting, trace drains and team-wide ZDR or provider allowlists at $0.10 per 1,000 requests on Pro and Enterprise.

Requesty is a unified AI gateway, LLM router and OpenAI-compatible API for 600+ models. Its homepage says it is used by 70,000+ developers processing 90+ billion tokens a day, and its docs describe routing across 30+ providers, although its pages state provider counts inconsistently. Pricing is simple: no per-seat fee and no minimum spend, you pay what your application spends plus a 5% markup, and failed requests are not charged.

Routing is policy-based. A bare model name is a managed policy that picks the best provider per request and fails over, and you can build fallback policies with up to 10 retries per model and exponential backoff, weighted load-balancing policies keyed on trace ID, and nested policies. Auto Cache adds cache breakpoints for providers that need them, with the cost savings stated as up to 80-90% on repeated prompts. Guardrails scan prompts for PII and secrets and can report or mask values, and BYOK works with OpenAI, Anthropic, Google AI Studio, Vertex AI, Mistral and xAI.

OrcaRouter is an OpenAI-compatible gateway for 200+ models that grades each prompt and can route it adaptively. You can ask orcarouter/auto to pick the cheapest live model that meets your bar, set routing rules as code in YAML and CEL, and configure fallback chains of up to five models that are tried on 5xx, 429 or network errors. It cites 40%+ inference cost savings from cache-aware adaptive routing, and its routing and latency claims are stated inconsistently across its pages.

It pairs routing with security and governance: guardrails for PII, secrets, jailbreaks and prompt injection, an agent firewall that allows, queues for human review or blocks tool and MCP calls, budgets, roles and an audit trail, request logs with cost and latency, prompt versioning and 32 compliance framework packs. Payments are provider price with a $0.00 routing fee, using pay as you go, a credit subscription or your own keys.

FastRouter is an LLM gateway and LLMOps platform that routes, compares and operates across 200+ models with a single OpenAI-compatible API, and also speaks the Anthropic Messages and Gemini native formats. Every tier, including the free Starter plan, passes model costs through with $0 markup. Its docs say 160+ models across 20+ providers, so the model count is stated two ways.

Routing options include lowest price, lowest latency, highest throughput, weighted shuffle, priority order and an AI auto router, with automatic retry of the next model or provider on rate limits, downtime or errors. Virtual model aliases map one stable name to many models, FastRouter Blend sends a prompt to several models and has a judge compare them, and prompt caching is included on all tiers. Response caching, guardrails in observe and validate modes, distributed tracing and alerts arrive on Pro and above.

Concentrate is a managed LLM gateway: one API for major model providers, with the headline "every model, every AI provider, no fees". Its docs say the API supports 168 models from 21 providers, though its marketing says hundreds. There is no platform markup on tokens and no service or credit-card fee, and you can bring your own provider keys to use your own credits or committed spend.

Its focus is spend and data control. Fallbacks follow an ordered chain you set across providers or models, and spend is tracked by organization, team, key, model and provider with limits by team or key and alerts for balances and unusual spend. Request logs show status, latency, tokens, cost and provider. Zero data retention can be enforced by provider, team or key, 104 models have at least one ZDR-certified provider, and PII, PCI and PHI can be redacted from prompts or responses.