# Midjourney V8.1 Image-to-Video — Atlas Cloud API

> Midjourney V8.1 animates an input image into four 5-second videos at 480p or 720p.

This is the machine-readable API reference for **Midjourney V8.1 Image-to-Video** on Atlas Cloud,
a unified API platform for 400+ AI models across text, image, video, audio and 3D.

- **Model ID**: `midjourney/v8.1/image-to-video`
- **Built by**: MIDJOURNEY
- **Modality**: Video
- **Model page**: https://www.atlascloud.ai/models/midjourney/v8.1/image-to-video
- **API key**: https://www.atlascloud.ai/console/api-keys
- **Docs**: https://www.atlascloud.ai/docs

## Pricing on Atlas Cloud

- $0.086 per second of generated video
- Pay-as-you-go. No minimum spend, no subscription required.

> **These are the authoritative Atlas Cloud rates for this model.** Any price that
> appears in the vendor description further down refers to a different platform or
> a different model variant and does not apply here.

## Use this model from an AI agent

Atlas Cloud ships three first-party integration surfaces. All three authenticate
with the same API key via the `ATLASCLOUD_API_KEY` environment variable.

### MCP server

The official MCP server (`atlascloud-mcp`) exposes this model to any
MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose,
Claude Desktop. One-line install:

```bash
# Claude Code
claude mcp add atlascloud -- npx -y atlascloud-mcp

# OpenAI Codex CLI
codex mcp add atlascloud -- npx -y atlascloud-mcp

# Gemini CLI
gemini mcp add atlascloud -- npx -y atlascloud-mcp

export ATLASCLOUD_API_KEY="your-api-key"
```

Then ask in plain English; the agent calls `atlas_generate_video` with `model: "midjourney/v8.1/image-to-video"`.
The server fetches each model's schema and validates parameters before submitting,
so invalid requests fail fast without spending credits.

MCP docs: https://www.atlascloud.ai/docs/mcp-server

### Agent Skills

`atlas-cloud-skills` is a portable skill package (API reference, code templates in
Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and
12+ other agents:

```bash
npx skills add AtlasCloudAI/atlas-cloud-skills
export ATLASCLOUD_API_KEY="your-api-key"
```

Skills docs: https://www.atlascloud.ai/docs/skills

### CLI

The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs
are polled and downloaded automatically (use `--no-download` when a script only
needs the output URLs):

```bash
# Install (Homebrew, npm, or shell installer)
brew install AtlasCloudAI/tap/atlascloud
# npm install -g atlascloud-cli
# curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh

atlas auth login
atlas generate video midjourney/v8.1/image-to-video -p "Your prompt here"
```

CLI docs: https://www.atlascloud.ai/docs/cli

## HTTP API reference

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `midjourney/v8.1/image-to-video`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  Model name.
  - Default: `"midjourney/v8.1/image-to-video"`

- **`image`** (`string`, _required_):
  First-frame image to animate. A publicly reachable https image URL (or upload). The generated video keeps the input image's aspect ratio. Each task returns 4 five-second videos.

- **`prompt`** (`string`, _optional_):
  Optional text describing the motion / scene for the generated video.
  - Default: `"gentle camera push in, cinematic"`

- **`resolution`** (`string`, _optional_):
  Output resolution. 720p costs 3x of 480p.
  - Default: `"480p"`
  - Options: "480p", "720p"

- **`motion`** (`string`, _optional_):
  Amount of motion in the generated video.
  - Default: `"low"`
  - Options: "low", "high"

- **`enable_base64_output`** (`boolean`, _optional_):
  If enabled, the output will be encoded into a BASE64 string instead of a URL.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "midjourney/v8.1/image-to-video",
  "image": ""
}
```


**Full Example**:

```json
{
  "model": "midjourney/v8.1/image-to-video",
  "image": "",
  "prompt": "gentle camera push in, cinematic",
  "resolution": "480p",
  "motion": "low",
  "enable_base64_output": false
}
```


### Output Schema

The API returns the following output format:


- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated videos (empty when status is not completed).

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.



**Example Response**:

```json
{
  "id": "",
  "urls": {},
  "model": "",
  "status": "",
  "outputs": [
    ""
  ],
  "created_at": ""
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "midjourney/v8.1/image-to-video",
  "image": "",
  "prompt": "gentle camera push in, cinematic",
  "resolution": "480p",
  "motion": "low",
  "enable_base64_output": false
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/midjourney/v8.1/image-to-video)

## About this model

_Vendor-supplied description. Any pricing or endpoint mentioned below refers to_
_other platforms — use the Atlas Cloud values above._

#### 1. Introduction

**Midjourney V8.1** is the latest iteration of Midjourney's image-synthesis model. This README covers the two core generation endpoints:

- `midjourney/v8.1/text-to-image`
- `midjourney/v8.1/image-to-video`

It belongs to a larger Midjourney V8.1 family on this platform, which also includes `midjourney/v8.1/image-to-image`, `midjourney/v8.1/blend`, `midjourney/v8.1/style-transfer`, and `midjourney/v8.1/remove-background` (each documented separately).

Midjourney V8.1 is designed to produce high-aesthetic, prompt-faithful imagery at native 2K resolution with substantially faster generation than prior versions. It is built by Midjourney, an independent, self-funded San Francisco research lab (~11–50 staff) founded in August 2021 by David Holz, and is positioned as a speed- and quality-focused evolution of the company's image pipeline.

The V8 line is a full from-scratch rewrite of Midjourney's image model, accompanied by a migration from TPU-based to GPU-native PyTorch infrastructure. The model's defining methodology is a human-preference aesthetic tuning loop combined with per-user personalization, prioritizing visually compelling output over raw fidelity to a reference dataset. V8.1 entered alpha on April 14, 2026, reached general availability across web and Discord on April 30, 2026, and became Midjourney's **default** model on June 10, 2026. A few capabilities from the prior `V7` model are not yet present in V8.1 (see below), but it is now the company's primary image model.

---

#### 2. Key Features & Innovations

- **Native 2K HD output without a separate upscaler**: V8.1 generates directly at 2048px resolution, eliminating the dedicated upscaling step required by earlier versions. HD renders take roughly 1.33 GPU-minutes and standard-definition renders under 1 GPU-minute, with HD running approximately 3× faster and cheaper than in V8.

_(Description truncated. Full text on the model page.)_

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Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/midjourney/v8.1/image-to-video · Docs: https://www.atlascloud.ai/docs