minimax/hailuo-2.3/fast

图生视频

Hailuo 2.3 Fast API by MiniMax

minimax/hailuo-2.3/fast

Fast

Speed-optimized variant of Hailuo-2.3 delivering rapid video generation while maintaining strong visual quality for quick iterations.

Hailuo 2.3 Fast 由 MiniMax 开发。Atlas Cloud（由 Atlas Cloud AI LLC 运营）仅提供接入服务，并不拥有该模型。所有商标均归其各自所有者所有。

输入

提示词

图片 *

可拖拽文件至此，或点击上传

MAX:1

时长

启用提示词扩展

快速模式

输出

空闲

生成的视频将在这里显示

配置参数后点击运行开始生成

每次运行将花费 $0.19。$10 可运行约 52 次。

你可以继续：

Seedance 2.0 Kling v3 Vidu Wan2.7

参数

代码示例
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "minimax/hailuo-2.3/fast",  # Required. model name
    "duration": 6,  # The duration of the generated media in seconds. options: 6 | 10
    "enable_prompt_expansion": True,  # The model automatically optimizes incoming prompts to enhance output quality
    "go_fast": True,  # Prioritize faster video generation speed with a moderate trade-off in visual quality
    "image": "example_value",  # Required. The model generates video with the picture passed in as the first frame
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # The positive prompt for the generation
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

安装

安装所需的依赖包。

pip install requests

认证

所有 API 请求需要通过 API Key 进行认证。您可以在 Atlas Cloud 控制台获取 API Key。

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

HTTP 请求头

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

保护好您的 API Key

切勿在客户端代码或公开仓库中暴露您的 API Key。请使用环境变量或后端代理。

提交请求

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

提交请求

提交一个异步生成请求。API 返回一个 prediction ID，您可以用它来检查状态和获取结果。

POST/api/v1/model/generateVideo

请求体

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "minimax/hailuo-2.3/fast",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

响应

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

检查状态

轮询 prediction 端点以检查请求的当前状态。

GET/api/v1/model/prediction/{prediction_id}

轮询示例

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

状态值

processing请求仍在处理中。

completed生成完成，输出可用。

succeeded生成成功，输出可用。

failed生成失败，请检查 error 字段。

完成响应

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

上传文件

将文件上传到 Atlas Cloud 存储，获取可在 API 请求中使用的 URL。使用 multipart/form-data 上传。

POST/api/v1/model/uploadMedia

上传示例

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

响应

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

以下参数在请求体中被接受。

总计: 6必填: 2可选: 4

modelstringrequired

model name

Default: "minimax/hailuo-2.3/fast"

durationinteger

The duration of the generated media in seconds.

Default: 6

610

enable_prompt_expansionboolean

The model automatically optimizes incoming prompts to enhance output quality. This also activates the safety checker, which ensures content safety by detecting and filtering potential risks.

Default: true

go_fastboolean

Prioritize faster video generation speed with a moderate trade-off in visual quality

Default: true

imagestringrequired

The model generates video with the picture passed in as the first frame.Base64 encoded strings in data:image/jpeg; base64,{data} format for incoming images, or URLs accessible via the public network. The uploaded image needs to meet the following conditions: Format is JPG/JPEG/PNG; The aspect ratio is greater than 2:5 and less than 5:2; Short side pixels greater than 300px; The image file size cannot exceed 20MB.

promptstring

The positive prompt for the generation.

请求体示例

{
  "model": "minimax/hailuo-2.3/fast",
  "duration": 6,
  "enable_prompt_expansion": true,
  "go_fast": true,
  "image": "example_image"
}

Output Schema

API 返回包含生成输出 URL 的 prediction 响应。

created_atstring

ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

idstring

Unique identifier for the prediction, the ID of the prediction to get.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content (empty when status is not completed).

statusstring

Status of the task: created, processing, completed, or failed.

响应示例

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills 将 400+ AI 模型直接集成到您的 AI 编程助手中。一条命令安装，即可用自然语言生成图像、视频和与 LLM 对话。

支持的客户端

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ 支持的客户端

安装

npx skills add AtlasCloudAI/atlas-cloud-skills

设置 API Key

从 Atlas Cloud 控制台获取 API Key，并将其设置为环境变量。

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

功能

安装后，您可以在 AI 助手中使用自然语言访问所有 Atlas Cloud 模型。

图像生成使用 Nano Banana 2、Z-Image 等模型生成图像。

视频创作使用 Kling、Vidu、Veo 等模型从文本或图像创建视频。

LLM 对话与 Qwen、DeepSeek 等大语言模型对话。

媒体上传上传本地文件用于图像编辑和图生视频工作流。

MCP Server

Atlas Cloud MCP Server 通过 Model Context Protocol 将您的 IDE 与 400+ AI 模型连接。支持任何兼容 MCP 的客户端。

支持的客户端

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ 支持的客户端

安装

npx -y atlascloud-mcp

配置

将以下配置添加到您的 IDE 的 MCP 设置文件中。

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

可用工具

atlas_generate_image从文本提示生成图像。

atlas_generate_video从文本或图像创建视频。

atlas_chat与大语言模型对话。

atlas_list_models浏览 400+ 可用 AI 模型。

atlas_quick_generate一步式内容创建，自动选择最佳模型。

atlas_upload_media上传本地文件用于 API 工作流。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "The AtlasCloud API."
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateVideo": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/result/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "minimax/hailuo-2.3/fast"
          },
          "duration": {
            "default": 6,
            "description": "The duration of the generated media in seconds.",
            "enum": [
              6,
              10
            ],
            "type": "integer",
            "x-ui-component": "select"
          },
          "enable_prompt_expansion": {
            "default": true,
            "description": "The model automatically optimizes incoming prompts to enhance output quality. This also activates the safety checker, which ensures content safety by detecting and filtering potential risks.",
            "type": "boolean"
          },
          "go_fast": {
            "default": true,
            "description": "Prioritize faster video generation speed with a moderate trade-off in visual quality",
            "type": "boolean"
          },
          "image": {
            "description": "The model generates video with the picture passed in as the first frame.Base64 encoded strings in data:image/jpeg; base64,{data} format for incoming images, or URLs accessible via the public network. The uploaded image needs to meet the following conditions: Format is JPG/JPEG/PNG; The aspect ratio is greater than 2:5 and less than 5:2; Short side pixels greater than 300px; The image file size cannot exceed 20MB.",
            "type": "string"
          },
          "prompt": {
            "description": "The positive prompt for the generation.",
            "maxLength": 2000,
            "type": "string"
          }
        },
        "required": [
          "model",
          "image"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "image",
          "duration",
          "enable_prompt_expansion",
          "go_fast"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).",
            "format": "date-time",
            "type": "string"
          },
          "id": {
            "description": "Unique identifier for the prediction, the ID of the prediction to get.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content (empty when status is not completed).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM 友好的提示词模板

# minimax/hailuo-2.3/fast

> Speed-optimized variant of Hailuo-2.3 delivering rapid video generation while maintaining strong visual quality for quick iterations.


## Overview

- **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**: `minimax/hailuo-2.3/fast`


## 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: `"minimax/hailuo-2.3/fast"`

- **`prompt`** (`string`, _optional_):
  The positive prompt for the generation.

- **`image`** (`string`, _required_):
  The model generates video with the picture passed in as the first frame.Base64 encoded strings in data:image/jpeg; base64,{data} format for incoming images, or URLs accessible via the public network. The uploaded image needs to meet the following conditions: Format is JPG/JPEG/PNG; The aspect ratio is greater than 2:5 and less than 5:2; Short side pixels greater than 300px; The image file size cannot exceed 20MB.

- **`duration`** (`integer`, _optional_):
  The duration of the generated media in seconds.
  - Default: `6`
  - Options: 6, 10

- **`enable_prompt_expansion`** (`boolean`, _optional_):
  The model automatically optimizes incoming prompts to enhance output quality. This also activates the safety checker, which ensures content safety by detecting and filtering potential risks.
  - Default: `true`

- **`go_fast`** (`boolean`, _optional_):
  Prioritize faster video generation speed with a moderate trade-off in visual quality
  - Default: `true`



**Required Parameters Example**:

```json
{
  "model": "minimax/hailuo-2.3/fast",
  "image": ""
}
```


**Full Example**:

```json
{
  "model": "minimax/hailuo-2.3/fast",
  "prompt": "",
  "image": "",
  "duration": 6,
  "enable_prompt_expansion": true,
  "go_fast": true
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”).

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

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

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

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

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



**Example Response**:

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


## 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": "minimax/hailuo-2.3/fast",
  "prompt": "",
  "image": "",
  "duration": 6,
  "enable_prompt_expansion": true,
  "go_fast": true
}'

# 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/minimax/hailuo-2.3/fast)

A powerful curved beam of light forcefully pierces through a transparent glass cube. The impact creates sharp refractions and scattering light rays. Fine cracks spread across the surface as shards subtly vibrate. Cinematic lighting, high contrast, volumetric light, ultra-detailed glass texture, slow motion.

加载中...

MiniMax Hailuo 2.3 — Fast Model

Hailuo 2.3 Fast is the high-speed version of MiniMax’s latest video generation model.

It produces cinematic-quality videos 30–50% faster than the standard model while maintaining stable motion, clear detail, and balanced lighting — ideal for creators who need both speed and quality.

⚡ Why It’s Great

Accelerated Generation – Create 6–10 second clips up to twice as fast as Hailuo 2.3 Standard.
High Efficiency, Low Cost – Perfect for batch content creation, previews, and iteration loops.
Consistent Quality – Despite faster generation, visual stability and motion smoothness remain impressive.
Safety & Prompt Expansion – Built-in safety checker and automatic prompt enhancement for optimal output.
Flexible Durations – Supports both 6-second and 10-second formats at 1080p clarity.

Model Details

Input: text prompt (optional reference image for stability)
Duration options: 6 seconds or 10 seconds
Resolution: 1080p
Prompt Expansion: optional auto-refinement to enhance quality
Processing speed: typically 20–50 seconds per clip

How to Use

Write your prompt describing the scene, lighting, or action.

Example: “A cute kitten stretches lazily in the morning sunlight, soft fur glowing.”
(Optional) Upload a reference image to fix the composition.
Select your duration (6 s or 10 s).
Enable Prompt Expansion for improved scene coherence and safety.
Check Go Fast mode to prioritize speed.
Click Run and receive your generated video in under a minute.

Pro Tips

Keep prompts concise — the model auto-expands them intelligently.
Use lighting cues like sunset, studio light, or cinematic glow for richer output.
For social content, try 6 s mode for faster delivery.
For detailed storytelling or dynamic motion, use 10 s.
Combine clips to create longer edits using consistent camera language.