---
title: "Append runs to an experiment"
method: POST
path: "/v2/experiments/{experiment_id}/runs"
tags: ["Experiments"]
---

# Append runs to an experiment

`POST /v2/experiments/{experiment_id}/runs`

Append new runs to an existing experiment.

**Payload Requirements**
- Provide between 1 and 1000 runs in `experiment_runs`.
- Each run must include:
  - `output` -- model/task output for the run
  - `example_id` -- the ID of an existing example in the dataset,
  required only when the experiment is associated with a dataset
  - You may include any additional fields per run that can be used for
  analysis or filtering. For example: `model`, `latency_ms`,
  `temperature`, `prompt`, `tool_calls`, etc.

**Valid example**
```json
{
  "experiment_runs": [
    {"example_id": "example_001", "output": "4", "model": "gpt-4o-mini"}
  ]
}
```

**Invalid example** (missing required output field)
```json
{
  "experiment_runs": [
    {"example_id": "example_001"}
  ]
}
```

<Note>This endpoint is in beta, read more [here](https://arize.com/docs/ax/rest-reference#api-version-stages).</Note>

## Path parameters

- `experiment_id` string, required — A universally unique identifier (base64-encoded opaque string).

## Request body

- InsertExperimentRunsRequest
  - `experiment_runs` ExperimentRunInput[], required — Array of experiment run data to append to the experiment. Between 1 and 1000 runs per request.
    - `example_id` string, nullable — ID of the dataset example associated with this experiment run. Provided when the experiment is associated with a dataset; omitted otherwise.
    - `output` string, required — output of the task for the matching example

## Response `201`

Experiment with the IDs of the newly inserted runs.

- ExperimentWithRunIds — Experiments combine a dataset (example inputs/expected outputs), a task (the function that produces model outputs), and one or more evaluators (code or LLM judges) to measure performance. Each run is stored independently so you can compare runs, track progress, and validate improvements over time. See the full definition on the Experiments page. Use an experiment to run tasks on a dataset, attach evaluators to score outputs, and compare runs to confirm improvements.
  - `id` string, required — Unique identifier for the experiment
  - `name` string, required — Name of the experiment
  - `space_id` string, required — Unique identifier for the space this experiment belongs to
  - `dataset_id` string, nullable — Unique identifier for the dataset associated with this experiment. Null if the experiment isn't associated with a dataset.
  - `dataset_version_id` string, nullable — Unique identifier for the dataset version associated with this experiment. Null if the experiment isn't associated with a dataset.
  - `created_at` string, date-time, required — Timestamp for when the experiment was created
  - `updated_at` string, date-time, required — Timestamp for the last update of the experiment
  - `experiment_traces_project_id` string — Unique identifier for the experiment traces project this experiment belongs to (if it exists)
  - `integration_id` string, nullable — Identifier (base64) of the agent integration that backs this experiment, as returned by the integrations API. Null for non-agent experiments (for example, SDK or Playground experiments).
  - `run_ids` string[], required — IDs of the newly inserted experiment runs, in input order.

## Other responses

- `400` — Invalid request
- `401` — Authentication is required
- `403` — Insufficient permissions to access this resource
- `404` — Not found
- `422` — Unprocessable entity
- `429` — Rate limit exceeded

---

[API](https://skmtc.net/arize-ai/apis/arize-rest-api.md) · [All operations](https://skmtc.net/arize-ai/apis/arize-rest-api/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/arize-ai/arize-rest-api/versions/2ce448f1de13/schema)