OpenAIGPT-4o API

Name: GPT-4o API
Price: 2.75 USD
Author: OpenAI

Multimodal GPT-4o — solid quality at low latency, no reasoning pass.

Prompt

Images

0/8 images

Billed at this model’s published rate.

Result

Other models from OpenAI

Same vendor, same API call — the differences are below.

Model	Use case	Price	Resolution	Duration	Added
GPT-6.1 Sol	Image → Text	from $0.10 / 1M cached in	—	—	Oct 2026
GPT-6.1 Terra	Image → Text	from $0.05 / 1M cached in	—	—	Oct 2026
GPT Image 2.6 Flare	Text → Image	from $40.00 / 1M output img tok	1K · 2K · 4K	—	Oct 2026
GPT Image 2.6 Sunburst	Text → Image	from $40.00 / 1M output img tok	1K · 2K · 4K	—	Oct 2026
GPT-6 Luna	Image → Text	from $0.011 / 1M cached in	—	—	Sep 2026
GPT-6 Sol	Image → Text	from $0.22 / 1M cached in	—	—	Sep 2026
GPT-4.1 Mini	Image → Text	from $0.44 / gen	—	—	Sep 2026
GPT-4.1 Nano	Image → Text	from $0.11 / gen	—	—	Sep 2026

Install the SDK

TypeScript targets Node 20+ and ships with types; Python needs 3.10+ and is async. Over REST there is nothing to install: call https://api.picsart.com from any HTTP client.

bash

npm install @picsart/ai-sdk

Authenticate

Send your Picsart API key as a bearer token. The SDK does it for you once the client is created.

import { createClient } from '@picsart/ai-sdk';

const ai = createClient({
  apiKey: process.env.PICSART_API_KEY, // sent as: Authorization: Bearer <key>
  apiUrl: 'https://api.picsart.com',
});

python

import os

from picsart_ai_sdk import create_client

ai = create_client(
    api_key=os.environ["PICSART_API_KEY"],  # sent as: Authorization: Bearer <key>
    api_url="https://api.picsart.com",
)

Make a request

Call the model by its id. Over REST, one endpoint serves every model: POST /workflows/v1/models/execute with the model id and its input in the body. The outer params is the envelope every workflow takes; the inner one is this model's input, with the same names generateText() / generate_text() takes.

import { createClient } from '@picsart/ai-sdk';

const ai = createClient({
  apiKey: process.env.PICSART_API_KEY,
  apiUrl: 'https://api.picsart.com',
});

const { text } = await ai.generateText('gpt-4o', {
  prompt: "A serene mountain lake at golden hour, ultra detailed"
});

console.log(text);

python

import asyncio
import os

from picsart_ai_sdk import create_client


async def main() -> None:
    async with create_client(
        api_key=os.environ["PICSART_API_KEY"],
        api_url="https://api.picsart.com",
    ) as ai:
        res = await ai.generate_text("gpt-4o", {
            "prompt": "A serene mountain lake at golden hour, ultra detailed",
        })

        print(res.text)


asyncio.run(main())

bash

curl -X POST 'https://api.picsart.com/workflows/v1/models/execute' \
  -H 'Authorization: Bearer $PICSART_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
  "params": {
    "model": "gpt-4o",
    "params": {
      "prompt": "A serene mountain lake at golden hour, ultra detailed"
    }
  }
}'

Parameters

2 parameters, the same for the SDK and for the inner params over REST. Required ones must be supplied; the rest fall back to their defaults.

Parameter	Type	Required	Default	Details
`prompt` The message or question for the model, in plain language. With input images, what to say about them.	`text`	yes	`—`	—
`imageUrls` Images for the model to look at, as URLs.	`file (image[])`	no	`—`	—

Response

generateText() resolves to the generated text. Over REST the output is at response.result, inside the gateway's status envelope with the task id, its status and the amount charged.

json

{
  "text": "…generated text…",
  "model": "gpt-4o"
}

Overview

Text models are also served through an LLM proxy that speaks each vendor's own API. Requests and responses — streaming included — pass through exactly as the vendor defines them, so code written against the vendor's API or official SDK works here by changing only the base URL and the API key.

The same model is also reachable through one OpenAI-compatible Chat Completions endpoint that serves Claude, GPT and Gemini alike — switch vendors by changing model. When you'd rather use Picsart's own parameter names, use the unified API.

Authenticate with your Picsart API key, as Authorization: Bearer <key> (see Authentication). Any vendor credentials you send are ignored.

Endpoints

All on https://api.picsart.com, with gpt-4o as the model id.

API	Endpoint	Request body
Chat Completions (unified)	`POST /llm-proxy/openai/v1/chat/completions`	OpenAI reference
Responses (native)	`POST /llm-proxy/openai/v1/responses`	Vendor reference

Chat Completions

One endpoint and one client for every text model, with the OpenAI SDK (pip install openai / npm install openai). The vendor is picked from model, so switching to another model means changing only that.

python

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["PICSART_API_KEY"],
    base_url="https://api.picsart.com/llm-proxy/openai/v1",
)

completion = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)

print(completion.choices[0].message.content)

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.PICSART_API_KEY,
  baseURL: 'https://api.picsart.com/llm-proxy/openai/v1',
});

const completion = await client.chat.completions.create({
  model: 'gpt-4o',
  messages: [{ role: 'user', content: 'Write a haiku about the ocean.' }],
});

console.log(completion.choices[0].message.content);

bash

curl -X POST 'https://api.picsart.com/llm-proxy/openai/v1/chat/completions' \
  -H "Authorization: Bearer $PICSART_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "gpt-4o",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'

Responses (native)

The vendor's own Responses API with the OpenAI SDK (pip install openai / npm install openai) — the request bodies are the vendor's own, unchanged.

python

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["PICSART_API_KEY"],
    base_url="https://api.picsart.com/llm-proxy/openai/v1",
)

response = client.responses.create(
    model="gpt-4o",
    input="Write a haiku about the ocean.",
)

print(response.output_text)

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.PICSART_API_KEY,
  baseURL: 'https://api.picsart.com/llm-proxy/openai/v1',
});

const response = await client.responses.create({
  model: 'gpt-4o',
  input: 'Write a haiku about the ocean.',
});

console.log(response.output_text);

bash

curl -X POST 'https://api.picsart.com/llm-proxy/openai/v1/responses' \
  -H "Authorization: Bearer $PICSART_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "gpt-4o",
  "input": "Write a haiku about the ocean."
}'

Rates

What this model costs per generation, in USD. Every row is an exact rate — the columns are the settings that change it.

Tier	Rate
Cache write	$0.00 / 1M cache write tokens
Cached input	$1.25 / 1M cached input tokens
Input	$2.50 / 1M input tokens
Generation	$2.75 / generation
Output text	$10.00 / 1M output text tokens

OpenAIGPT-4o API

Params

Result

Other models from OpenAI

Install the SDK

Authenticate

Make a request

Parameters

Response

Overview

Endpoints

Chat Completions

Responses (native)

Rates