8 Best LiteLLM Alternatives in 2026 (Compared)

LiteLLM is a great way to start calling 100+ LLM providers through one API. It's also a Python proxy you have to deploy, scale, patch, and monitor yourself — plus Redis for caching, Postgres for spend tracking, a second instance for high availability, and a config file that grows every time someone adds a model.

That operational bill is why most teams start searching for LiteLLM alternatives. The proxy works; owning it is the problem.

We compared the eight LiteLLM alternatives teams actually switch to in 2026 — on the things that matter: whether you can self-host or must trust a cloud, what the gateway costs on top of provider prices, how routing and failover work, and how much infrastructure you're signing up to run. We build one of them, so we're biased — but we'll tell you where each option genuinely wins.

Why Teams Look for LiteLLM Alternatives

The complaints are consistent:

• You become the platform team. The proxy is yours to deploy, scale, upgrade, and page yourself about at 3 a.m. None of that work ships product.
• Config sprawl. Model lists, fallback chains, budgets, and virtual keys all live in YAML that grows with every team that adopts it.
• Enterprise features are paywalled. SSO, audit logs, and advanced admin controls sit behind LiteLLM Enterprise — so "free and open source" stops being free right when you need governance.
• Python overhead at scale. At high request volumes, the Python runtime becomes the bottleneck, and you solve it with more replicas and more ops.

If none of that bothers you, keep LiteLLM — it's a solid library, especially in-process from Python. If it does, here are the alternatives.

What to Look for in a LiteLLM Alternative

Four questions separate the options fast:

1. Managed, self-hosted, or both? The whole point of leaving LiteLLM is usually shedding ops — but some teams still need the option to run it themselves.
2. What does it cost on top of provider prices? In 2026 no serious gateway marks up tokens. The competition is platform fees and BYOK terms.
3. Is routing smart or manual? Fallback lists you maintain by hand versus routing that weighs uptime, latency, and price for you.
4. Are governance features included or gated? Audit logs, guardrails, and team management are exactly the features that get paywalled.

Comparison Table

1. LLM Gateway

Best overall. Open source, self-hostable, zero BYOK markup.

LLM Gateway is the closest thing to "LiteLLM without the ops." It's an open-source (AGPLv3) gateway that routes to 200+ models across 40+ providers through one OpenAI-compatible endpoint — available as a managed cloud where the proxy, caching, analytics, and billing are already wired together, or self-hosted with a single Docker command.

What sets it apart:

• Both deployment models — use the managed cloud and run zero infrastructure, or self-host the same AGPLv3 codebase on your own machines
• Zero markup on BYOK — bring your own provider keys and pay nothing on top of provider costs
• Smart routing, not fallback lists — providers are scored on uptime, throughput, price, and latency; failed requests retry and fail over transparently
• Guardrails on the Enterprise plan — prompt-injection, PII, jailbreak, and secret detection built into the gateway, no external integration to wire up
• Team management built in — roles, projects, audit logs, and per-key limits are part of the product
• Built-in caching and analytics — Redis-backed response caching plus per-request cost, latency, and cache-hit dashboards

Because both sides speak the OpenAI API, migrating from LiteLLM is a two-line change:

1import OpenAI from "openai";2
3const client = new OpenAI({4  baseURL: "https://api.llmgateway.io/v1",5  apiKey: process.env.LLM_GATEWAY_API_KEY,6});

1import OpenAI from "openai";2
3const client = new OpenAI({4  baseURL: "https://api.llmgateway.io/v1",5  apiKey: process.env.LLM_GATEWAY_API_KEY,6});

Pricing: Free to self-host. Managed cloud is pay-as-you-go with a 5% platform fee on credits — or 0% with your own provider keys.

Best for: Teams that picked LiteLLM for openness and control but don't want to operate a proxy fleet to keep them. See the full LLM Gateway vs LiteLLM breakdown or the feature-by-feature comparison.

2. OpenRouter

Managed routing with the largest model catalog.

OpenRouter is the zero-infrastructure route: one API key, roughly 400+ models across 70+ providers, and no proxy to run. If your main LiteLLM complaint is ops, this is the simplest exit.

Strengths:

• Huge catalog, including community and fine-tuned models
• OpenAI-compatible API with usage tracking and request-level analytics
• No per-token markup; provider prices pass through

Weaknesses:

• Not open source and no self-hosting — a hard stop for some LiteLLM users
• 5.5% fee on credit purchases; BYOK is free only up to 1M requests/month, then 5%
• Response caching is still in beta

Pricing: Pay-as-you-go with a 5.5% credit-purchase fee.

Best for: Developers who want maximum model variety with zero infrastructure and don't need to self-host.

3. Bifrost

The fastest open-source proxy swap.

Bifrost (from Maxim AI) is a self-hosted, open-source gateway written in Go — the most direct like-for-like LiteLLM replacement on this list. Its pitch is raw efficiency: the project benchmarks its overhead in microseconds per request at thousands of requests per second, where Python proxies are measured in milliseconds.

Strengths:

• Open source and self-hosted, like LiteLLM — but a single Go binary instead of a Python service
• Very low routing overhead at high request volumes
• Governance features (virtual keys, budgets) in the open-source core

Weaknesses:

• You still own the infrastructure — this solves LiteLLM's performance complaint, not the ops one
• Younger project with a smaller community and integration ecosystem
• No managed cloud; observability is thinner than platform gateways

Pricing: Free and open source; you run it. Paid support via Maxim.

Best for: Teams that want to keep self-hosting and mainly need more throughput per node than a Python proxy delivers.

4. Portkey

Enterprise governance, now part of Palo Alto Networks.

Portkey is an AI gateway aimed at enterprises: deep request tracing, guardrails, budgets, and compliance controls. Gateway 2.0 (March 2026) open-sourced most of the governance and observability stack under MIT, with persistent storage and compliance features remaining in the managed cloud. Palo Alto Networks acquired Portkey in May 2026, folding it into Prisma AIRS.

Strengths:

• Mature observability: traces, logs, and cost attribution
• Guardrails and policy controls suited to compliance-heavy teams
• Much of the platform is now MIT-licensed

Weaknesses:

• Full platform still requires their cloud for log storage and compliance features
• Usage-based pricing (from $49/month plus per-log fees) adds up at volume
• Now part of a large security vendor — a plus for some buyers, a lock-in concern for others

Pricing: Free tier; Production from $49/month plus $9 per 100k logs; enterprise by quote.

Best for: Enterprises that want governance and observability first and are comfortable inside a large vendor's security portfolio.

5. Vercel AI Gateway

Zero markup, native to the AI SDK.

Vercel AI Gateway routes to hundreds of models across 45+ providers and has been GA since 2025. It's the default provider for the Vercel AI SDK, with both OpenAI- and Anthropic-compatible endpoints.

Strengths:

• Zero markup on tokens, including BYOK
• First-class AI SDK integration — if you use streamText, it just works
• Failover, caching, and spend monitoring built in

Weaknesses:

• Managed only — no open source, no self-hosting
• Tied to a Vercel team account; some governance features cost extra
• Least compelling if you're not already in the Vercel ecosystem

Pricing: Pay-as-you-go credits with no token markup.

Best for: Teams building on the Vercel AI SDK who want the shortest path off a self-hosted proxy.

6. Kong AI Gateway

LLM routing as plugins on API infrastructure you already run.

Kong AI Gateway extends Kong's API gateway with AI plugins: multi-LLM routing, semantic caching, prompt guarding, and token-based rate limiting. If Kong already fronts your APIs, your platform team can manage LLM traffic with the tooling they know.

Strengths:

• One gateway layer for APIs and LLMs — same plugins, same observability, same team
• Semantic caching and prompt-security plugins
• Self-hostable open-source core plus the managed Konnect platform

Weaknesses:

• Heavyweight if you don't already run Kong — you'd be adopting an API platform to get an LLM proxy
• LLM features are plugins on a general-purpose gateway, not a purpose-built product
• No provider billing layer; you manage provider keys and spend elsewhere

Pricing: Open-source gateway is free; AI features expand under paid Konnect and Enterprise tiers.

Best for: Platform teams already standardized on Kong who want LLM traffic under the same roof.

7. TrueFoundry

Kubernetes-native gateway inside your own VPC.

TrueFoundry ships an AI gateway as part of its broader ML platform, deployed Kubernetes-native in your own cloud account with RBAC, budgets, and governance. It advertises low single-digit-millisecond overhead at hundreds of requests per second per vCPU.

Strengths:

• Runs entirely in your VPC — data never leaves your boundary
• Enterprise governance: RBAC, quotas, audit, cost controls
• Part of a full ML platform if you also need training and deployment tooling

Weaknesses:

• Not open source, and buying it means an enterprise sales motion
• Overkill if you only need a gateway rather than an ML platform
• You still operate the Kubernetes footprint it runs on

Pricing: Enterprise; by quote.

Best for: Enterprises with strict data-residency requirements and an existing Kubernetes practice.

8. Cloudflare AI Gateway

Edge caching and cost visibility for Cloudflare shops.

Cloudflare AI Gateway proxies LLM requests through Cloudflare's edge, adding caching, rate limiting, retries, and per-request analytics with minimal setup — point your provider's base URL at it and you're done.

Strengths:

• Trivial setup if you're on Cloudflare; generous free tier
• Edge caching and rate limiting close to users
• Useful cost and latency analytics per provider

Weaknesses:

• A visibility-and-caching layer more than a routing gateway — no smart multi-provider failover
• No self-hosting, no BYOK billing layer, limited provider management
• Basic feature set compared to purpose-built gateways

Pricing: Free core features with a Cloudflare account; paid tiers for higher limits.

Best for: Teams already on Cloudflare who want caching and observability, not full routing.

Two Names You Can Skip in 2026

Older "LiteLLM alternatives" lists still recommend two products you should no longer adopt:

• Helicone was acquired by Mintlify in March 2026 and is in maintenance mode. Fine if you already run it; the wrong choice for a new deployment.
• Unify shut down its LLM router and pivoted to AI agents. It's no longer a gateway.

If a comparison article lists either as an active gateway, check its publish date.

How to Choose

You want LiteLLM's openness without its ops: LLM Gateway is the only option that's open source, self-hostable, and offered as a managed cloud with zero BYOK markup.

You want zero infrastructure, maximum models: OpenRouter, if self-hosting isn't a requirement.

You want to keep self-hosting but need more throughput: Bifrost is the lightest like-for-like proxy swap.

You're buying for a compliance team: Portkey or TrueFoundry, depending on whether you want a managed platform or your own VPC.

You already run Kong or Cloudflare: Their AI gateways get you caching and controls with the least new vendor surface — just know their routing is thinner.

Whatever you pick, check the fee structure before you commit — see our breakdown of who marks up your tokens and the wider best AI gateways comparison.

Migrating Off LiteLLM

Every gateway on this list speaks the OpenAI API, so the mechanical migration is small — usually a base URL and API key change. The real work is recreating your routing rules, budgets, and virtual keys. LLM Gateway maps them directly: fallback chains become smart routing, spend tracking becomes per-project analytics, and virtual keys become scoped API keys. The LiteLLM migration guide walks through each piece.

Frequently Asked Questions

What is the best open-source LiteLLM alternative?

LLM Gateway (AGPLv3) is the most complete open-source alternative — the self-hosted version includes the dashboard, caching, guardrails, and analytics, not just the proxy. Bifrost is the best minimal option: a fast Go proxy you operate yourself.

Why do teams switch away from LiteLLM?

Operations and gating. LiteLLM makes you run, scale, and monitor a Python proxy plus its Redis and Postgres dependencies, and features like SSO and audit logs require its paid enterprise tier. Teams switch when the proxy starts consuming real engineering time.

How hard is it to migrate from LiteLLM?

The API call is a two-line change, since both LiteLLM and its alternatives expose OpenAI-compatible endpoints. Budgets, virtual keys, and fallback configs need to be recreated in the new gateway — see the migration guide.

Is Helicone still a good LiteLLM alternative?

Not for new deployments. Helicone entered maintenance mode after its 2026 acquisition by Mintlify. For observability with active development, LLM Gateway and Portkey both include request-level analytics.

Try the Top Pick

If you want LiteLLM's flexibility without running the infrastructure:

• Try LLM Gateway free — no credit card required, point your SDK at https://api.llmgateway.io/v1
• Read the LiteLLM migration guide — routing rules, keys, and budgets mapped one-to-one
• LLM Gateway vs LiteLLM — the detailed head-to-head if you're still deciding