# Instant ID Generate Avatar

Instant ID is making realistic images of real people instantly

## API Information

- **Model Slug:** instant-id
- **Branded URL:** https://www.eachlabs.ai/tencent/instant-id/instant-id
- **Provider:** Tencent
- **Category:** Image to Image
- **Output Type:** array
- **Status:** active
- **Version:** 0.0.1
- **Base Cost:** Per-second pricing based on provider predict_time. Rate: $0.00108/sec from GPU tier.
- **Estimated Processing Time:** 32 seconds
- **Last Updated:** 2026-04-06
- **Interactive Demo:** https://www.eachlabs.ai/ai-models/instant-id

## Pricing

- **Charge Type:** dynamic
- **Pricing Details:** Per-second pricing based on provider predict_time. Rate: $0.00108/sec from GPU tier.

### Pricing Rules

| Condition | Pricing |
| --- | --- |
| Rule 1 | Per-second pricing based on provider predict_time. Rate: $0.00108/sec from GPU tier. |

## Input Schema

| Parameter | Type | Required | Default | Constraints | Description |
|-----------|------|----------|---------|-------------|-------------|
| image | string | Yes | - | image/jpeg, image/png, image/jpg, image/webp | Input face image |
| pose_image | string | No | - | - | (Optional) reference pose image |
| prompt | string | No | a person | - | Input prompt |
| negative_prompt | string | No | - | - | Input Negative Prompt |
| num_inference_steps | integer | No | 4 | 1–4 | Number of denoising steps |
| sdxl_weights | string | No | stable-diffusion-xl-base-1.0 | stable-diffusion-xl-base-1.0,juggernaut-xl-v8,afrodite-xl-v2,albedobase-xl-20,albedobase-xl-v13,animagine-xl-30,anime-art-diffusion-xl,anime-illust-diffusion-xl,dreamshaper-xl,dynavision-xl-v0610,guofeng4-xl,nightvision-xl-0791,omnigen-xl,pony-diffusion-v6-xl,protovision-xl-high-fidel | An enumeration. |
| width | integer | No | 640 | 640–4096 | Width of output image |
| height | integer | No | 640 | 640–4096 | Height of output image |
| scheduler | string | No | EulerDiscreteScheduler | DEISMultistepScheduler,HeunDiscreteScheduler,EulerDiscreteScheduler,DPMSolverMultistepScheduler,DPMSolverMultistepScheduler-Karras,DPMSolverMultistepScheduler-Karras-SDE | An enumeration. |
| guidance_scale | number | No | 7.5 | 1–50 | Scale for classifier-free guidance |
| ip_adapter_scale | number | No | 0.8 | 0–1 | Scale for image adapter strength (for detail) |
| controlnet_conditioning_scale | number | No | 0.8 | 0–1 | Scale for IdentityNet strength (for fidelity) |
| enable_pose_controlnet | boolean | No | true | - | Enable Openpose ControlNet, overrides strength if set to false |
| pose_strength | number | No | 0.4 | 0–1 | Openpose ControlNet strength, effective only if `enable_pose_controlnet` is true |
| enable_canny_controlnet | boolean | No | false | - | Activates a specific control mechanism that uses edge detection to guide image generation. |
| canny_strength | number | No | 0.3 | 0–1 | Canny ControlNet strength, effective only if `enable_canny_controlnet` is true |
| enable_depth_controlnet | boolean | No | false | - | Enable Depth ControlNet, overrides strength if set to false |
| depth_strength | number | No | 0.5 | 0–1 | Depth ControlNet strength, effective only if `enable_depth_controlnet` is true |
| enable_lcm | boolean | No | false | - | Enable Fast Inference with LCM (Latent Consistency Models) - speeds up inference steps, trade-off is the quality of the generated image. Performs better with close-up portrait face images |
| lcm_num_inference_steps | integer | No | 5 | 1–10 | Only used when `enable_lcm` is set to True, Number of denoising steps when using LCM |
| lcm_guidance_scale | number | No | 1.5 | 1–20 | Only used when `enable_lcm` is set to True, Scale for classifier-free guidance when using LCM |
| enhance_nonface_region | boolean | No | true | - | Enhance non-face region |
| seed | integer | No | - | - | Random seed. Leave blank to randomize the seed |
| disable_safety_checker | boolean | No | false | - | Disable safety checker for generated images |

## Example Request

```bash
curl -X POST https://api.eachlabs.ai/v1/prediction/ \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "instant-id",
  "input": {
    "image": "https://storage.googleapis.com/magicpoint/inputs/jensen-huang.webp"
  }
}'
```

## Output Schema

Response returned by `GET /v1/prediction/{id}` when the job completes:

```json
{
  "status": "success",
  "predictionID": "string",
  "output": "array",
  "metrics": {
    "predict_time": "number (seconds)"
  }
}
```

## Polling

```bash
curl https://api.eachlabs.ai/v1/prediction/{PREDICTION_ID} \
  -H "X-API-Key: YOUR_API_KEY"
```

| Status | Meaning |
|--------|---------|
| `processing` | Still running — poll again |
| `success` | Done — read `output` |
| `error` | Failed — read `message` / `details` |

## Webhook (alternative to polling)

Pass `"webhook_url": "https://your.host/path"` in the create request. Eachlabs POSTs this payload when the job ends:

```json
{
  "exec_id": "prediction-uuid",
  "status": "succeeded",
  "output": "https://...",
  "error": ""
}
```

`status` is `"succeeded"` or `"failed"`. `exec_id` equals the `predictionID` from create. Return 2xx within 30 seconds.

## Errors

Error body: `{ "status": "error", "message": "...", "details": "..." }`

| Code | Meaning |
|------|---------|
| `400` | Invalid input |
| `401` | Missing / invalid `X-API-Key` |
| `404` | Unknown model or prediction id |
| `429` | Rate limit — 100 creates / min, 10 concurrent per key |
| `5xx` | Retry with backoff |

## Overview

**instant-id — Image-to-Image AI Model**

instant-id from Tencent delivers realistic image-to-image transformations, enabling instant generation of photorealistic depictions of real people from reference photos and text prompts. Part of Tencent's instant-id family, this **image-to-image AI model** excels at preserving facial identity and details, solving the challenge of creating consistent, high-fidelity portraits without extensive training data. Developers and creators searching for **Tencent image-to-image** solutions find instant-id ideal for rapid, accurate edits in e-commerce and content pipelines.

Powered by Tencent's advanced multimodal architecture, instant-id supports seamless reference-based generation, producing outputs that maintain intricate facial features, expressions, and lighting from input images. This makes it a go-to for **image-to-image AI model** applications requiring identity consistency across modifications.

## Usage Notes

- API Base URL: `https://api.eachlabs.ai/v1`
- Authentication: send `X-API-Key: YOUR_API_KEY`. Generate a key from the Eachlabs dashboard at https://www.eachlabs.ai/dashboard/api-keys.
- File-typed parameters (`*_url`, `image_url`, `video_url`, `audio_url`, etc.) accept publicly-reachable HTTPS URLs only. Upload your asset first (GCS / S3 / your CDN) and pass the resulting URL. Data-URIs and localhost URLs are rejected.
- For structured parameters (arrays / objects) send real JSON values, not stringified payloads.
- Monetary values are reported in USD; per-token / per-megapixel rates may be billed in micro-cents internally.
- Prefer `webhook_url` over polling for long-running predictions — see the Webhook Callback section.