--- title: "BYO API Key vs. Included AI Credits in n8n Hosting" description: "n8n Cloud, Elestio, Sliplane all require your own API key. See what that really costs vs. n8n hosting with AI credits already included and 350+ models." canonical: https://agentroost.app/en/blog/byo-api-key-vs-included-ai-credits-n8n date: 2026-05-18T04:00:00Z --- [Canonical URL](https://agentroost.app/en/blog/byo-api-key-vs-included-ai-credits-n8n) # BYO API Key vs. Included AI Credits in n8n Hosting When you start evaluating n8n hosts, the pricing page usually looks clean: a monthly fee, some compute specs, maybe a note about "unlimited executions." The AI bill isn't on that page. It shows up later — on your OpenAI invoice, or when a workflow silently fails because you hit a rate limit at 2 AM. There are exactly two models for how AI billing works inside a hosted n8n instance. Understanding the difference before you pick a host saves a lot of retrofitting. --- ## Model 1: Bring Your Own API Key (Every Major Host Today) n8n Cloud, Elestio, Sliplane, and Hostinger all follow the same pattern: they give you the n8n instance, and you wire up AI nodes by pasting your own API key from OpenAI, Anthropic, or whichever provider you use. This sounds fine in theory. In practice, it creates several compounding problems. ### The surprise bill problem n8n's AI nodes — the **AI Agent** node, the **OpenAI** node, the **LangChain** sub-graph nodes — call the provider API on every execution. If a workflow runs on a schedule every 15 minutes and chains two LLM calls, the token spend adds up fast. And it's unpredictable: a workflow that worked fine for weeks suddenly touches a larger document, or a loop misfires and calls the LLM far more times than intended. Your API spend that day can spike dramatically. Nothing in the n8n interface warns you in advance; you find out when the OpenAI dashboard sends an alert — or when the invoice closes. ### The key rotation problem API keys have a lifespan. Security-conscious teams rotate them periodically. Every rotation means: 1. Generate a new key in the provider dashboard. 2. Find every n8n credential that references the old key. 3. Update it. Test each workflow. 4. Revoke the old key. With one workflow this is a short job. With many workflows across multiple credential sets, it becomes a real operational burden. And when you need to migrate your instance to a different host, you're re-entering all of them. ### The rate-limit problem OpenAI, Anthropic, and Google all enforce rate limits per API key — requests-per-minute and tokens-per-minute ceilings that vary by account tier. New API accounts start with low ceilings. A workflow with a loop that processes many items simultaneously will hit the RPM limit, get a `429` error, and either retry-storm or silently skip rows depending on how the error handler is set up. Unlocking higher rate-limit tiers requires meeting cumulative spend thresholds on the provider's platform. You pay to unlock the right to pay more. ### The model-lock problem When you hard-code a specific model into a credential, switching to a different provider means creating a new credential set, updating every node that used the old one, and re-testing. Most teams end up locked on whatever model they started with because the switching cost feels higher than it's worth. --- ## Model 2: Included AI Credits (What It Actually Looks Like) The alternative is a host that bundles AI spend into the subscription price itself. Instead of connecting your own API key, the AI nodes in your n8n instance point to the host's LLM proxy — already authenticated, already paid for as part of your plan. The practical differences: **No credential setup.** When you drop an **AI Agent** node or an **OpenAI** node into your canvas, you select the host's built-in credential. It works immediately. No key, no provider account, no billing profile to set up. **No surprise bills.** Your monthly cost is the subscription. The AI usage is covered within the plan's included credit allocation. You know what you're paying before the month starts. **Model switching without key juggling.** If the host's proxy surfaces 350+ models, switching from GPT-4o to Claude Sonnet to Llama 3.3 is a dropdown change in the node — not a credential migration. You can run A/B prompt tests across models inside the same workflow using an **IF** node or a **Switch** node to route to different model names. **No rate-limit cliff from fresh accounts.** The host aggregates usage across their infrastructure. You're not starting from zero with rock-bottom limits on a brand-new provider account. --- ## Head-to-Head Comparison | Factor | BYO API Key | Included AI Credits | |---|---|---| | Upfront setup | Paste key, set up billing | None — works out of the box | | Monthly cost predictability | Variable (usage-dependent) | Fixed with the plan | | Surprise bills | Yes — loops, doc size spikes | No | | Key rotation burden | Manual, across all credentials | N/A | | Model switching | New credential per provider | Dropdown in the node | | Rate limits | Per-account (start low) | Host-aggregated | | New-user friction | Medium (need provider account) | Low | | Control / BYOK option | Full | Depends on host | The BYO model is not wrong — it makes sense if you already have substantial API credits from a prior deal, if you need a specific model the host's proxy doesn't expose, or if you want direct provider relationships for compliance reasons. But for most teams running n8n for internal automation, the included model removes an entire layer of operational overhead. --- ## How to Tell Which Model a Host Uses The easiest signal: look at the "get started" docs. If the first few steps include "go to OpenAI, create an account, add a payment method, generate an API key," it's BYO. If the AI nodes are described as working without any credential setup, credits are included. A secondary signal: check whether the host's pricing page mentions anything about AI or LLM usage. BYO hosts have nothing to say about it because it's not their problem. A host with included credits will call it out because it's a meaningful part of the value. --- ## How It Works on AgentRoost AgentRoost gives you **your own n8n instance** — your login, your workflows, your data, running at `https://.agentroost.app`. You own it, same as self-hosting, without the DevOps. The AI credits are included in the subscription. Here's the actual journey: 1. Sign up at [agentroost.app](/en/pricing) — email, Google, Microsoft, or Discord. 2. Pick the **n8n** framework, give your instance a name. 3. Your private n8n editor opens. Build your first workflow. 4. Drop in an **AI Agent** node or an **OpenAI** node. Select the built-in AgentRoost credential. It works — no key, no provider account. 5. Need a different model? Switch the model name in the node. 350+ options, same credential. Webhooks get a public HTTPS URL automatically. No Nginx config, no certificate renewal. The AI nodes are already wired. Plans start at **$19.99/mo all-in** — compute, hosting, and AI credits in one line item. There's a 14-day money-back guarantee and you can cancel anytime. If you're evaluating whether the included-credits model fits your workload before committing, the [pricing page](/en/pricing) breaks down what each tier includes, and [the n8n page](/en/agents/n8n) walks through what's pre-configured out of the box. 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