Understanding execution credits
An execution credit represents one node-minute of execution: the amount of time a node takes to run each time it executes. Credits are consumed both while you build a workflow (manual runs) and while it runs in production. Arranging and configuring nodes on the canvas without running them doesn't consume credits.
For example, a workflow with 11 nodes, each taking one minute to run, consumes 11 credits per execution.
Execution compute classes
The execution compute class moderates the execution credits a workflow consumes. Based on the chosen compute class, it uses a multiplier to determine how many execution credits a workflow consumes. This can be set individually for each workflow.
Available compute classes:
| Compute class | Multiplier | When to use it |
|---|---|---|
| Light | 0.6x | Workflows that aren't time-sensitive, to save credits. |
| Standard | 1x | The default compute resources for most workflows. |
| Fast | 1.6x | Time-sensitive workflows that need more computational resources. |
The default compute class "Standard" has a multiplier of 1 which means that one node-minute equals exactly one execution credit. For less time-sensitive work and to save credits, you can choose compute class "Light", where one node-minute equals 0.6 execution credits. If you need your workflows to complete faster, you can choose compute class "Fast", where one node minute equals 1.6 execution credits. This means, a workflow with 11 nodes, each taking one minute to execute, will consume 11 credits in compute class "Standard", 6.6 credits in compute class "Light", and 17.6 credits in compute class "Fast".
Does waiting for data consume credits?
- Waiting for external data (for example, a file from a third party) doesn't have to consume credits. Design the workflow to start only once the data has arrived — trigger it when a file is dropped, have the external process call Knime directly, or schedule the run for a time you know the data is ready. Avoid using a Wait node in production: it's intended for debugging and testing, not for production workflows.
- Waiting on in-database processing (for example, a step pushed to Snowflake or Databricks) does consume credits, because the workflow is still orchestrating that step as part of your pipeline. If cost is a concern and the workflow isn't time-sensitive, run it at the Light speed class.
Execution bands
Execution bands are your annual credit allowance: You commit to an execution band with a fixed number of execution credits at a fixed price at the start of your subscription period. Choose the band that fits your team's needs. There are up to 10 predefined bands, plus custom bands for consumption beyond that — your Knime account team can help you estimate usage and choose the right one.
An execution band is an allowance, not a stockpile of credits you receive. You can use up to the band's limit, but unused credits don't roll over or get refunded, similar to a mobile data plan or a car rental's kilometer package.
You can upgrade your band at any time by contacting your Knime account team — not only at renewal.
Understanding AI credits
We measure AI consumption in AI credits which are measured from the number of tokens used by the underlying LLMs, plus a service fee. One AI credit refers to 10,000 input tokens or 1,667 output tokens. Token usage translates into AI credit bands, each with its own price.
Similar to execution bands, you choose an annual AI capacity band which is your annual credit allowance for AI usage.
If you bring your own AI model, you pay your AI provider for tokens directly, and pay Knime a reduced service fee (0.17 credits) instead of the standard AI credit rate.
What happens if you reach your band limit
Knime notifies you as you approach your limit, and gives you room to keep working rather than cutting you off immediately:
| Usage | What happens |
|---|---|
| 60%, 80%, 100% of band | Notifications are sent. This is a good time to talk to your Knime account team about your band. |
| Up to 5% over (grace period) | No change. You keep working as usual; this is just a signal that you're in overage. |
| 5–20% over (throttling) | AI requests are limited to one every five minutes, and execution speed is reduced to the minimum speed class on each executor. |
| More than 20% over | Execution is suspended. |
At any point, even while suspended, you can upgrade to the next band to resume normal work immediately.
Sovereign execution credits
For sovereign execution environments, consumption still follows the same node-minute model, but with two differences:
- A flat fee applies per environment, in addition to credit consumption. If you have both a level 1 and a level 2 environment, both flat fees apply.
- Compute classes don't apply. Instead, a fixed multiplier (0.9 or 0.95, depending on the level) applies to every execution, since Knime can no longer control execution speed on infrastructure it doesn't manage.