OpenLLM vs OpenRouter: How to choose

OpenLLM and OpenRouter both advertise one endpoint for many models, so at feature-grid distance they look interchangeable. The choice actually comes down to where your AI spend lives. OpenRouter is a cloud marketplace for models you access through their accounts, priced as a percentage of credits. OpenLLM is a control plane for the accounts you already have, subscriptions included, priced flat. This guide works through where the two diverge on model access, economics, failover, custody, and setup, so the right call for your workflow is clear by the end.

Key takeaways:

• OpenRouter is a hosted marketplace: instant access to 400+ models through their credits, with a fee on credit purchases. It gives you breadth you don't have accounts for.
• OpenLLM connects the providers you already pay for, subscriptions and API keys alike, behind one endpoint for free up to 50M tokens a month, or $30/mo flat for Pro, with no token markup.
• Subscriptions are the structural difference. If most of your spend is a Claude plan, a ChatGPT plan, or a Kimi plan, a credits marketplace cannot route it. OpenLLM connects those accounts through each provider's own official apps.
• Failover differs in kind, not degree: OpenRouter routes between providers in their cloud, while OpenLLM's fallback chains move a failed request to the next plan or key in your chain before any output starts, so an agent keeps working instead of stopping on a rate limit.
• Neither is cheaper in every case. Light API-credit usage favors OpenRouter below about $545/mo. Two $100 subscriptions plus $30 of OpenLLM is roughly $20,000/mo of API-equivalent usage, which a credits marketplace cannot route.

Where OpenLLM and OpenRouter differ

The sharpest difference sits underneath both products. OpenRouter's unit of value is their accounts: you buy credits, they hold the provider relationships, and you rent access to a very large catalog. OpenLLM's unit of value is your accounts: your subscriptions, your API keys, your billing relationships, unified behind one key. That single split explains most of what follows, from who holds custody of credentials to what happens when a provider rate-limits you mid-task.

What this comparison is based on

This comparison draws on each product's public documentation and pricing pages. OpenRouter facts were checked against their published pricing at the time of writing; verify against their live pages, since fees change. Where OpenLLM behavior is described, it reflects the shipping product. We build OpenLLM, so read the conclusions with that in mind; the factual rows are checkable either way.

• Runs. OpenLLM: Local daemon on your machine + managed cloud. OpenRouter: Their cloud.
• Model access. OpenLLM: Every provider you hold an account with, plus any OpenAI/Anthropic-compatible endpoint. OpenRouter: 400+ models via their marketplace accounts.
• Subscription plans (Claude, ChatGPT, Kimi). OpenLLM: Supported through official provider apps, locally, your credentials. OpenRouter: Not supported; credits and API only.
• Fees. OpenLLM: free up to 50M tokens a month, Pro $30/mo flat, 0% on usage. OpenRouter: ~5.5% fee on credit purchases; BYOK free up to $25,000/mo of list-price inference, then 5%.
• Token prices. OpenLLM: Provider list prices; billing never touches us. OpenRouter: Provider list prices via their credits.
• Key custody. OpenLLM: Zero-knowledge vault: ciphertext at rest, unlock derived from your key per request. OpenRouter: Keys and credits held by OpenRouter.
• Failover. OpenLLM: Fallback chains across your plans, keys and local models. OpenRouter: Provider routing within their cloud, per request.
• Coding-agent setup. OpenLLM: One line; auto-configures Claude Code, Codex, Grok Build, OpenCode, Raycast. OpenRouter: Manual base-URL configuration.
• Beyond chat. OpenLLM: MCP for images, video, embeddings; memory across chats. OpenRouter: Chat/completions catalog.
• Best fit. OpenLLM: Devs whose spend is in subscriptions + a few providers, running coding agents daily. OpenRouter: Devs who want maximum catalog breadth without opening provider accounts.

Model access: breadth versus custody

OpenRouter's catalog is genuinely its moat. Four hundred plus models behind one key, including long-tail and open-weight models you would never open a direct account for, with public rankings that have become an industry reference. If your work is model exploration, evaluation, or you need something exotic this afternoon, that breadth is the product, and it is real.

OpenLLM's access model is narrower on catalog and wider on account types. It routes to whatever you hold: Claude, ChatGPT, Kimi, and Grok subscriptions, Anthropic and OpenAI API keys, and any OpenAI- or Anthropic-shaped endpoint you bring, which includes OpenRouter itself as a custom endpoint in a chain. New models on your connected providers appear without an update.

The economics, honestly

If you only buy API credits, OpenRouter is cheaper below about $545/mo, full stop. A 5.5% fee on $100 of credits is $5.50 against our flat $30. The fee reaches $30 at roughly $545 of credit spend and keeps growing while a flat fee doesn't. If that describes your usage, use OpenRouter, sincerely.

That comparison only applies to credits. Subscriptions are a different wallet, and they are the larger one for people running coding agents. Two $100 plans, Claude Max and ChatGPT Pro, plus $30 of OpenLLM is $230/mo. Routed through OpenLLM, that same stack is roughly $20,000/mo of API-equivalent usage: you keep the plans you already pay for, instead of buying the tokens again at list price. A credits marketplace cannot route those subscriptions at all. OpenLLM was built for exactly that wallet: connect the plans and keys you already pay for, route everything through one endpoint, and pay a flat fee for the software rather than a cut of usage.

Failover: across providers versus within one marketplace

Both products keep you off a single point of failure, but they do different things when failure arrives. OpenRouter can route a request to another provider serving the same or a similar model inside their cloud. That is retry-level resilience, and it works.

OpenLLM's fallback chains are built for long-running agent work. When a provider is down, rate-limited, out of quota, or the request is bigger than its context window, the chain moves to the next model in your list before any output starts, and the agent never sees the error. Requests that would overflow a model's context are skipped instead of paid for. One honest limit: once a reply has started streaming, it stays on that provider, because splicing two models into one answer would be worse than the failure. For chat apps the difference is minor. For an agent that hits a rate limit at minute forty, it is the difference between an interruption and a stopped task.

Custody and trust

With OpenRouter, custody is theirs by design: your credits, and any BYO keys, live in their cloud, and that simplicity is part of the appeal. With OpenLLM, credentials are ciphertext at rest and the unlock material is derived from your own key at request time, used in memory, and wiped. A dump of our database reveals nothing. The daemon, the component that touches your credentials, is open source and auditable. Which posture you prefer is a real choice, not a gotcha: a hosted marketplace is simpler to reason about; a zero-knowledge vault plus an auditable local component is stronger custody.

OpenRouter is a model marketplace

OpenRouter is a hosted API in front of 400+ models from dozens of providers, paid through credits, with public model rankings and a large developer ecosystem. One key, enormous catalog, no provider accounts to open.

Pros: unmatched model breadth; instant access to new and open-weight models; useful public rankings; simple mental model; BYOK free up to $25,000/mo of list-price inference. Cons: percentage fee scales with usage; cannot route subscription plans; keys and billing custody live in their cloud; fallback stays within their catalog; generic setup for coding agents.

Best for: developers and teams who want the widest possible catalog without opening provider accounts, experimenters, and anyone whose AI spend is entirely API-shaped and light enough that a small percentage beats a flat fee.

OpenLLM is a control plane for the accounts you already pay for

OpenLLM is a local daemon plus managed cloud that puts every model you pay for behind one endpoint: subscriptions connected through each provider's official apps with your own credentials, API keys in a zero-knowledge vault, and any compatible endpoint you bring. Aliases map names like ultra or reviewer to ordered fallback chains, editable live. One-line setup wires up Claude Code and friends; the MCP adds images, video, and embeddings inside your CLI; memory persists across sessions; and one dashboard shows cost across every provider. Free for 50M tokens a month, or $30/mo flat for Pro after a 3-day trial, no token markup, your accounts bill at their normal prices.

Pros: routes subscriptions no marketplace can touch; flat fee with 0% on usage; fallback across your own plans and keys; zero-knowledge custody with an auditable open-source daemon; agent-native setup; model switching inside your CLI to compare outputs. Cons: catalog limited to providers you hold accounts with; $30 is a worse deal than a percentage for light API-only usage; no self-hosted cloud; single-user today, teams on the roadmap.

Best for: developers who already pay for two or more AI plans or providers, run coding agents daily, and want their whole stack behind one key with custody and flat economics.

When to choose each

Choose OpenRouter when your spend is API credits under about $545/mo, you want catalog breadth over account custody, or you need occasional access to models you'd never open an account for. It is the better marketplace, and it isn't close.

Choose OpenLLM when your money is already going to subscriptions and a couple of providers, your agents need to survive provider failures mid-task, and you'd rather pay flat for software than a percentage of growing usage. It is the better control plane for accounts you own.

Use both when you want marketplace breadth inside owned-account custody: add OpenRouter as a custom OpenAI-compatible endpoint and drop it into a fallback chain.

How OpenLLM handles agent routing in production

Four patterns show up for almost everyone running coding agents daily.

Provider outages mid-task. The next request goes to the next model in the chain, so the agent keeps working instead of stopping on an error.

Fragmented keys and spend. Subscriptions, keys, and custom endpoints behind one key, with per-provider, per-model cost in one dashboard.

Model comparison friction. Switch aliases inside Claude Code to run the same prompt across Opus, GPT-5.6, and Kimi without leaving the session, including for multi-model review graphs where reviewers from different labs catch what same-model review misses.

New-model lag. New models on your connected providers show up in your model list without an update.

FAQs

Does OpenLLM mark up tokens? No. Your accounts bill at provider prices; the $30/mo is the only thing we charge.

Is routing subscriptions allowed? OpenLLM connects subscription accounts through each provider's own official apps, locally, with your credentials, and our terms prohibit pooling, resale, and limit evasion. You remain responsible for your provider terms, and API keys work everywhere.

Can I use OpenRouter through OpenLLM? Yes. Add it as a custom OpenAI-compatible endpoint (their base URL plus your OpenRouter key) and put it in a fallback chain.

What happens when the trial ends? It converts to Pro at $30/mo unless you cancel, which takes one click. The free plan stays available.

One line to install, under five minutes to your first routed request: openllm.sh