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Moondream3 Preview [Point] Large Language Models

fal-ai/moondream3-preview/point
Moondream 3 is a vision language model that brings frontier-level visual reasoning with native object detection, pointing, and OCR capabilities to real-world applications requiring fast, inexpensive inference at scale.
Inference
Commercial use
PlaygroundAPI

About

Point Object Detection

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/moondream3-preview/point", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/moondream-3-preview/point_in.jpg",
    prompt: "bottle caps"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

3. Queue#

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/moondream3-preview/point", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/moondream-3-preview/point_in.jpg",
    prompt: "bottle caps"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/moondream3-preview/point", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/moondream3-preview/point", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Read more about file handling in our file upload guide.

5. Schema#

Input#

image_url string* required

URL of the image to be processed

Max width: 7000px, Max height: 7000px, Timeout: 20.0s

prompt string* required

Object to be located in the image

{
  "image_url": "https://storage.googleapis.com/falserverless/example_inputs/moondream-3-preview/point_in.jpg",
  "prompt": "bottle caps"
}

Output#

finish_reason string* required

Reason for finishing the output generation

usage_info UsageInfo* required

Usage information for the request

points list<Point>* required

List of points marking the detected objects

{
  "finish_reason": "stop",
  "usage_info": {
    "output_tokens": 23,
    "decode_time_ms": 811.5944429300725,
    "input_tokens": 737,
    "ttft_ms": 91.87838807702065,
    "prefill_time_ms": 54.45315001998097
  },
  "points": [
    {
      "y": 0.8660801564027371,
      "x": 0.11827956989247312
    },
    {
      "y": 0.8660801564027371,
      "x": 0.3118279569892473
    },
    {
      "y": 0.8660801564027371,
      "x": 0.5953079178885631
    },
    {
      "y": 0.8758553274682307,
      "x": 0.7888563049853372
    },
    {
      "y": 0.5796676441837733,
      "x": 0.9423264907135875
    },
    {
      "y": 0.5796676441837733,
      "x": 0.6324535679374389
    },
    {
      "y": 0.6021505376344086,
      "x": 0.44281524926686217
    },
    {
      "y": 0.5982404692082112,
      "x": 0.3010752688172043
    },
    {
      "y": 0.4701857282502444,
      "x": 0.20332355816226785
    },
    {
      "y": 0.4506353861192571,
      "x": 0.053763440860215055
    },
    {
      "y": 0.6021505376344086,
      "x": 0.053763440860215055
    }
  ]
}

Other types#

Object#

x_min float* required

Left boundary of detection box in normalized format (0 to 1)

y_min float* required

Top boundary of detection box in normalized format (0 to 1)

x_max float* required

Right boundary of detection box in normalized format (0 to 1)

y_max float* required

Bottom boundary of detection box in normalized format (0 to 1)

UsageInfo#

input_tokens integer* required

Number of input tokens processed

output_tokens integer* required

Number of output tokens generated

prefill_time_ms float* required

Time taken for prefill in milliseconds

decode_time_ms float* required

Time taken for decoding in milliseconds

ttft_ms float* required

Time to first token in milliseconds

Point#

x float* required

X coordinate of the point in normalized format (0 to 1)

y float* required

Y coordinate of the point in normalized format (0 to 1)

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