Top 5 LiteLLM alternatives in 2026

Your LiteLLM proxy works. Then Postgres needs a migration, Redis needs a failover plan, and someone has to vet the next release. At some point the gateway becomes a part-time job.

LiteLLM's open-source version is free, per its pricing page. The engineer time to run it isn't, and neither is spend you can't see by team or feature.

Five managed large language model (LLM) gateways can take that work off your plate. Each one trades something for it, like API format, spend controls, or the ability to run inside your own network.

What you run when you self-host LiteLLM

In production, a LiteLLM proxy is a small platform, not a single container. LiteLLM's own production guide names a database, a cache, sized pods, and secrets handling, and each one needs an owner and an on-call plan.

In March 2026, LiteLLM disclosed a suspected supply chain incident. It says attackers likely uploaded two malicious releases (1.82.7 and 1.82.8) directly to the Python Package Index (PyPI), and that users of its proxy Docker image weren't affected (LiteLLM security update). A self-hosted gateway puts release hygiene on your team.

Some features also sit on the paid plan. LiteLLM lists single sign-on (SSO), System for Cross-domain Identity Management (SCIM), and audit logs under its Enterprise plan.

What self-hosting costs in engineer time

The license is free, but the upkeep repeats every month. Each piece of the stack turns into work someone on your team owns:

• Upgrades: pin and test each release, then run migrations
• Database and cache: keep PostgreSQL and Redis healthy
• Secrets: guard and rotate the master key and provider keys
• Capacity: resize pods as traffic grows
• On-call: someone answers when the gateway is down

Track those hours for one month. That's the number to compare against a managed gateway's fees.

What changes when you go managed

Going managed moves the database, cache, upgrades, and uptime to a vendor. Keys, budgets, fallbacks, and logs become product settings instead of services you configure. You give up one thing: the gateway no longer runs inside your own network.

That trade shapes the whole decision. Before you compare vendors, answer two questions:

• Can your traffic leave your network? If a policy says it can't, a managed gateway won't fit.
• Which API format do your clients call? LiteLLM's proxy is OpenAI-compatible, so many clients call Chat Completions. Not every gateway accepts it.

Who owns AI spend after the move?

A gateway is also where you control AI spend, so decide who owns it before you pick one. Engineering sets the limits, and finance needs to see the result.

• Limits: Who sets a cap on each key, team, or user, and who can raise it?
• Attribution: Can you tag requests by feature, team, and environment so finance can allocate the bill?
• Reporting: Do logs show cost per request, or only token counts?

For context, read what drives unexpected AI token cost increases and how AI token spend compares across businesses.

Five managed gateways, and what each one takes off your plate

1. Ramp Router

Ramp Router is a hosted gateway built by Ramp. Your app uses one Router key, and Router holds the provider credentials. Its docs describe "One OpenAI Responses-compatible API for all models across providers," and it also accepts Anthropic Messages requests (API reference).

What you stop running: the proxy and everything behind it. Router handles the jobs your proxy did:

• Spend caps: set a lifetime or recurring cap on each key, and lock, unlock, or revoke it (control spend)
• Labels: tag requests by feature, team, and environment, so spend rolls up the way finance reports it
• Fallbacks: list 1 to 15 models (fallbacks guide)
• Logs: see which fallbacks Router tried (monitor and debug)

What to check:

• API format: Router doesn't support Chat Completions, so clients that call it move to /v1/responses
• Hosting: it isn't self-hostable, and per its FAQ all models run on U.S.-based infrastructure
• Signup: it needs a business email and domain (signup eligibility)
• Models: the model directory lists each model's list price, context window, and capabilities, so check it for the models you use
• Keys: Gemini requires your own key. BYOK works for OpenAI, Gemini, Fireworks, xAI, Baseten, and Sail Research, with Anthropic listed as coming soon.

Cost: Router is pay-per-token. You pay the provider's list price for tokens bought through Ramp, with no separate Router fee on non-BYOK traffic. BYOK traffic has no fee today, and Router is free through 2026.

Ramp also offers AI Token Spend Management, which tracks spend across providers like Anthropic, OpenAI, and Gemini and lets finance set limits and alerts. For a starting plan, read how to reduce AI token costs and how Ramp helps you see, understand, and control AI spend.

2. OpenRouter

OpenRouter is a hosted gateway. Its quickstart describes "hundreds" of models behind one endpoint, automatic fallbacks, and an OpenAI SDK drop-in path.

What you stop running: the proxy, database, and cache. Clients that already call Chat Completions often keep the same request shape, which makes it the closest hosted match to a LiteLLM proxy.

What to check: the docs we reviewed didn't state per-key or per-team spend caps. If you rely on LiteLLM budgets today, confirm how you'd enforce them.

Cost: per OpenRouter's FAQ, there's no markup on inference. A 5.5% fee ($0.80 minimum) applies to credit purchases, and 5% for crypto. BYOK is free up to a $25,000 monthly allowance, then 5%.

3. Portkey (now PRISMA AIRS AI Gateway)

Portkey describes a unified AI platform with a gateway for "over 250 AI models" and observability across requests. The gateway is also open source per its docs, which keeps a self-hosting option open. Palo Alto Networks completed its acquisition of Portkey in 2026.

What you stop running: on its managed plans, the proxy and the pipeline that ships your logs to a monitoring tool. The docs list ISO 27001 and SOC 2 certification, which can shorten a security review.

What to check: ownership changed in 2026, so confirm roadmap and pricing with the vendor. Features also differ between the open-source and managed versions.

Cost: Developer is free for 10K recorded logs a month. Production is $49 a month for 100K recorded logs, plus $9 per additional 100K up to 3M. Enterprise is custom.

4. Cloudflare AI Gateway

Cloudflare AI Gateway helps you "observe and control your AI applications," and works with providers including Workers AI, Anthropic, Google Gemini, OpenAI, and Replicate.

What you stop running: your own caching and rate-limit layer. Analytics, logging, caching, rate limiting, retry, and fallback all run on Cloudflare's network.

What to check: the docs overview doesn't describe per-key or per-team budgets or which API formats it accepts. Confirm both before you move traffic.

Cost: per Cloudflare's docs, core features (dashboard analytics, caching, and rate limiting) are free on all plans. Logpush needs the Workers Paid plan. Unified Billing adds a 5% fee on credit purchases, and inference passes through without markup (Cloudflare pricing).

5. Vercel AI Gateway

Vercel AI Gateway centralizes credentials, request logs, spend budgets, and provider failover. Your app doesn't need to run on Vercel (Vercel docs).

What you stop running: the proxy, database, and cache. It accepts the AI SDK, Chat Completions, Responses, and Anthropic Messages, so mixed clients can share one gateway. Budgets can be set for a team, project, API key, or team member.

What to check: per its docs, budgets cover spend billed through Vercel's system credentials, and BYOK spend is metered separately.

Cost: no markup and no platform fee on tokens. You pay the provider's list price from a prepaid balance. Some add-ons, such as custom reporting and team-wide zero data retention (ZDR), carry separate per-request charges .

Which API formats and spend limits each gateway documents

Map each LiteLLM job to a question for the new gateway

A move goes smoothly when you list what your proxy does, then ask the new gateway one question per job. Use this as your checklist.

Then move one service at a time. Send a small share of real traffic through the new gateway, compare cost reporting and failure behavior, and retire the proxy only after traffic is stable. If you go to Router, the Connect guide shows the base URL (https://api.router.com/v1) and how to convert Chat Completions fields to Responses. Router model IDs are account-specific, so pull them from GET /v1/models.

When to stay on LiteLLM

Staying put is the right call in a few cases. If traffic can't leave your network, a managed gateway won't fit. If your platform team already runs the database and cache for other services, the extra load may be small. And if you need a LiteLLM-specific feature like its agent-to-agent (A2A) and Model Context Protocol (MCP) gateway, check that your target supports it first.

For everyone else, the question is whether running the proxy is the best use of your engineers.

Pick by what you need to stop doing

Move your LLM spend controls to Ramp Router

Ramp Router gives you one key, a spend cap on each key, and request logs across providers, with no proxy to run. If a provider fails, Router moves to the next model on your fallback list.

Ramp Router works with the OpenAI Responses and Anthropic Messages APIs, and its coding agents guide covers setup for Claude Code, Codex, OpenCode, Pi, Hermes, Conductor, and Cursor.