GPT-5 Nano is a lightweight language model from the GPT-5 family designed for rapid text generation with low latency and cost-effective performance, ideal for real-time applications.

How fast is the model's performance?

GPT-5 Nano is optimized for high-speed text generation, making it exceptionally suited for applications such as chatbots and real-time content processing.

Do I need to include an image URL?

No, including an image URL is optional. The primary requirement is the `prompt` field, which drives the text generation process.

How cost-effective is GPT-5 Nano?

With a cost of $0.01 per generation, GPT-5 Nano offers one of the most affordable pricing options in the market while maintaining superior quality and performance.

Does this model support Prompt Caching?

Yes. Prompt Caching allows you to reuse frequently used text prompts at reduced rates. Cache hits (reusing previously cached tokens) are charged at 0.1x of the input cost. New cache creation (writing new tokens to cache for future reuse) is charged at 1.25x of the standard input cost.

Back to Comparison Hub/GPT5 Nano Text Pricing

Text to Text

GPT5 Nano Text API Pricing

GPT-5 Nano is a lightweight, high-speed language model from the GPT-5 family designed for instant text generation. It delivers intelligent, context-aware responses for creative writing, summarization, dialogue, code generation, and automation — all at low latency and cost. Perfect for chatbots, assistants, content tools, and real-time applications that need fast, reliable text output.

Savings Alert33% ↓Cheaper than Fal.ai

About GPT5 Nano Text

GPT-5 Nano is a state-of-the-art, lightweight language model engineered for lightning-fast text generation. As part of the GPT-5 family, it leverages advanced deep learning techniques to deliver intelligent and context-aware responses that are ideal for a range of applications, from creative writing and summarization to dialogue, code generation, and automation. Designed with low latency in mind, GPT-5 Nano enables real-time interactions without compromising on performance, making it a preferred choice for chatbots, digital assistants, and other dynamic content tools. Beneath its compact architecture, GPT-5 Nano harnesses sophisticated neural network strategies that ensure both efficiency and scalability. Its technical innovation, combined with cost-effective pricing, provides unique advantages over bulkier models without sacrificing quality. With an emphasis on smart, context-sensitive output generation, this model not only meets the technical demands of real-time applications but also offers a seamless user experience for creative and commercial projects alike.

Interactive Savings Calculator

Estimate monthly API spend and compare absolute developer savings.

Monthly API Generations10,000 runs

50025,00050,00075,000100,000+

MuAPI Monthly Cost

$100.00

$0.01 per generation

Fal.ai Cost

$150.00

$0.015 per generation

Estimated Monthly Savings$50.00

Annual Savings$600.00

Detailed Pricing Breakdown

Provider	Estimated Rate	Notes
muapiapp	$0.01 per generation	muapiapp offers this service at a cost that is 20-50% more affordable than other providers, delivering comparable or superior quality. Supports Prompt Caching (0.1x for hits, 1.25x for creation).
Fal.ai	$0.015 per generation	Fal.ai charges around $0.015 per generation, making muapiapp 33% more cost-effective while ensuring equivalent performance and output quality.
Replicate	$0.015 per generation	Replicate's pricing stands at about $0.015 per generation; muapiapp is 20-50% cheaper, offering competitive performance at an irresistible price point.

Developer Integration Snippets

import requests
import time
import json

api_key = "YOUR_API_KEY"
url = "https://api.muapi.ai/workflow/run/gpt-5-nano"

def poll_for_result(run_id):
    url = f"https://api.muapi.ai/workflow/run/{run_id}/api-outputs"
    headers = {
        "Content-Type": "application/json",
        "x-api-key": f"{api_key}",
    }
    while True:
        response = requests.get(url, headers=headers)
        result = response.json()

        if result['status'] == 'completed':
            return json.loads(result['outputs'])

        if result['status'] == 'failed':
            raise Exception(result.get('error', 'Generation failed'))

        time.sleep(5)

data = {
  "schemas": {
    "input_data": {
      "x-order-properties": [
        "prompt",
        "image_url"
      ],
      "type": "object",
      "properties": {
        "prompt": {
          "examples": [
            "Write a short story about a time traveler who accidentally visits the wrong century and becomes a painter instead of a scientist."
          ],
          "description": "Text prompt describing the text.",
          "type": "string",
          "title": "Prompt",
          "name": "prompt"
        },
        "image_url": {
          "examples": [
            null
          ],
          "description": "URL of the input image.",
          "field": "image",
          "type": "string",
          "title": "Image URL",
          "name": "image_url"
        }
      },
      "title": "Text",
      "required": [
        "prompt"
      ],
      "endpoint_url": "gpt-5-nano"
    },
    "output_data": {
      "x-fal-order-properties": [
        "text"
      ],
      "type": "object",
      "properties": {
        "video": {
          "examples": [
            "Arin Vale hadn’t intended to land in a painting, and certainly not in Florence during the drift of a season’s end when the city wore the yellow of sunlit plaster like a tired old coin. The Chronometer—a ring of copper etched with constellations and a dial that heated when you spoke of future weather—had promised a jump to 2087, where climate data braided with city planning and time itself kept a tidy ledger. Instead, when the device coughed and winked, Arin found their breath tasting of olive oil and dust, and the square before them stretching with columns and awnings that seemed to lean toward the light. It was the year 1532, or so a street peddler claimed when Arin asked for the date in a voice that trembled with disbelief.\n\nThe city wore the scent of hot stone, wet pigments, and a rumor of rain that would never come that day. The Chronometer’s hum faded to a polite sigh and then to silence, leaving Arin with nothing but a marble-slick sense of wrongness and a backpack full of instruments that felt absurdly fragile in this world of bread ovens and open wells. Arin had studied weather, cycles, and the way a city breathed when the wind turned from the east; here, the wind carried dust from the river and the gossip of apprentices circling a wooden scaffold.\n\nThe first sight that snagged Arin’s eye wasn’t a clock or a river, but a painter’s studio tucked into a narrow alley where the sun pressed two fingers of light through the window. A man with a brush held in an oddly practiced grip—hands stained brown with pigment and a stubborn line of ink at the corner of his mouth—stood over a panel of fish scales and gesso. On the easel, a city of lines and shadow seemed to ripple in the heat. Arin clutched the Chronometer, then slipped it into a pocket and stepped closer. The air was bright with the sting of pigment and sweat, and for a fraction of a breath, Arin felt something like a spark flare: not the cold certainty of a scientist verifying a model, but the warm, listening curiosity of someone who could learn a life by looking.\n\n“Signore,” Arin began, using the Italian the device had suggested was polite, though it sounded strange in their own mouth. “I am not here to steal, only to learn.” The painter looked up, eyes narrowing not with suspicion so much as a wary suspicion of a stranger’s intent.\n\nThe master—named Lorenzo, as the apprentice introduced him later—had a workshop that breathed like a living thing: a breath of resin and oil, a chorus of scraping brushes, the soft clack of a cup against a saucer, a cat that slept in a sunbeam and woke with a stretch. The apprentice, a wiry girl with a fringe of hair that kept slipping into her eyes, watched Arin with a mix of fearless curiosity and polite reserve. They were not in a place where you announced you came from the future; you were in a place where you earned bread by the brush and a patron’s smile by not asking questions about distant skies.\n\n“I am a student of the heavens,” Arin found themselves saying, perhaps to fill the silence, or perhaps because the lie felt safer than the truth. “I study how light travels, how colors shift, how a city ages in a season.” It was not a lie exactly—just an oblique path to the real truth, which was that Arin had intended to bring back measurements that might guide cities to survive heat and flood. But the word “heavens” hung there like a question mark, inviting a response.\n\nThe studio talk shifted as the apprentice—whose name was Mara—grinned and nudged Arin toward the palette. “We mix pigments,” Mara said, half-chiding, half-welcoming. “We do not measure time, yet we count it by the number of days a painting holds a breath.” It was a way to say: this is how you learn to see, not to calculate.\n\nArin fell into painting as if waking from a dream of a city flooded with data. They learned to grind pigments with a mortar, to bind them with egg and resin, to temper panels until they sang with a certain readiness to accept a story. The studio smelled of almonds and dogwood, of sun-bleached linen and the old, stubborn truth that paint can carry more than color: it can carry a memory of light. The scientific mind kept trying to map the pigments, to catalog the layers, to compare different whites—lead white, white earth, ochre, and the pale luminosity that glowed in a sunset. But in the rhythm of the day—the lifting of a veil of dust from a balcony, the way the light pressed on the corner of a doorway, the quiet arithmetic of perspective—Arin found another calculation that mattered more: how to see.\n\nDays bled into weeks, and Arin’s identity shifted from traveler of futures to student of the past’s pigment. They learned to measure distance with a painter’s eye, to coax light into a canvas by building gentle geometry into the frame. The master was strict, yet kind, and Mara teased a bright, stubborn fondness that suggested Arin might stay, not because the machine broken beyond repair was a fate, but because the life of canvas and color offered a kind of certainty the future had never granted.\n\nOne morning, finished with a study of a street corner, Arin stood back from a panel and realized something: the data they had anxiously carried in their mind—the climate curves and the models of storm tracks—had not vanished; they had learned to translate that data into something that could travel without a machine. Light, in this era, did not travel in the same way as across the hundreds of miles of a modern map; it finished its journey on the eye, and the eye, in turn, finished the journey on the canvas. Arin’s notes grew less scientific and more lyrical: a chart of shadows, a graph of brightness across the day, a narrative of color that moved like weather.\n\nThe moment of conversion came on a night when the studio was open to the patrons of the square, a small gallery night that felt like a pulse in the living heart of the city. A duke’s courier arrived with a commission for a painting of the city as it might be seen in a calm year, a future year, a year that could coax both greed and gratitude from the onlookers. The master asked Arin to lead the effort, to be the one who translated the moonlight and the bustle into something that could tell a story with eyes instead of instruments.\n\nArin did not begin by describing climate models or sea-salt winds; instead, they painted a scene that hummed with life. A street, at dusk, where the lamp light spilled golden on the stones, and in a corner stood a figure, half-inside, half-outside the painting, gazing toward a city’s far horizon. The figure bore the faintest suggestion of something not quite human: a silhouette of a man with a ring on his finger, a ring that seemed to glow with an inner weather—the kind of glimmer Arin had studied in spectral diagrams but never before dared to translate into color. The painting was not a direct forecast but a language of possibility—an image that might be seen and felt by someone who did not know the science, yet who understood the weather in a way the sciences never fully captured.\n\nWhen the duke’s men returned to view the work, they whispered about color, about light, about how the painting held a breath that would not end. The master’s face, usually a mask of quiet pride, softened into something close to reverence. Mara clapped softly, and the courtyard of that evening rang with the muted sound of approving voices.\n\nArin began to suspect something might happen to them beyond the studio’s doors: a choice about a future that no longer belonged to a future-borne traveler but to a person who had found a home in a medium that could outlive a century. The Chronometer hummed again one night when a storm rolled over the city. It flickered with a stubborn glow, and Arin stood at the window, watching rain strike the tiles with a patient, rhythmic clap. The device begged for recalibration, begged for permission to rewrite a path. But Arin did not reach for it. The work offered an answer that a formula never could: art as a mapping of time, not the timekeeper itself.\n\nThe decision unfolded in a quiet scene, a late-evening studio with the last ember of the day glowing in the oil lamp. Mara and Lorenzo asked if Arin would stay, to teach the apprentices and to help sustain the studio that had become more a crossroads of memory than a business. There was a murmur, as if the walls themselves were listening, waiting for a consent. Arin looked at the room—the brushes, the jars, the stacked canvases that glowed softly in the lamplight—and felt something like a verdict pressed into their bones: I will stay. Not to study the future by force of a machine, but to honor the present the way light honors a surface, by staying until the moment it reveals itself fully.\n\nThe Chronometer never sang again. Not in public, not in Arin’s presence. It remained a stubborn, inert ring that hummed whenever Arin brushed a stroke to the edge of a panel. Some days, Arin wondered if it would ever function again, and some days, the painting seemed to answer: you already did the work you needed to do.\n\nYears later, visitors would walk through the studio and see Arin’s canvases: panels that glowed with the quiet brilliance of season and streetlight, portraits that kept a city’s memory alive in oil and pigment, landscapes of weather made not in data but in the way light waited on stone. People spoke of Arin as a painter who could listen to the atmosphere and translate it into color with a science that was not a set of measurements but a discipline of perception.\n\nSometimes a scholar would come to study the painter’s technique, to trace how Arin’s early fascination with charts and graphs had become a different kind of chart—a map of perception, where time was measured not by clocks but by the shifting quality of light across a canvas. In those moments, Arin would smile and say nothing about the Chronometer, except that time traveled in the mind when the eye learned to see what science could not fully capture.\n\nIn a small ledger kept behind a false drawer in the studio, there is a line written in Arin’s hand: Time is not only something that happens to us; it is something we learn to paint. The page is spare, almost shy, but it hints at a pact: that to arrive in a century unplanned can be a misfortune or a revelation, and that sometimes a traveler’s greatest duty is to learn a language that makes the world legible to the heart.\n\nIf you stood before one of Arin’s late works and asked what it meant, you might hear a soft answer: a voice as gentle as a lamp’s glow and as certain as a line that won’t bend. It would tell you nothing of dates or weather models, but everything about looking, about how a life can pivot when the world invites you to see differently. And if you listened long enough, you might hear the city answering back—a chorus in pigment, a chorus of shadows that says, in the old tongue of light and matter, that time travels not only through years but through what we choose to hold onto: the moment when a traveler trades a laboratory for a studio, and discovers that the best way to change the future is to paint it, one careful stroke at a time."
          ],
          "description": "The generated prompt",
          "title": "Text",
          "comparison": false
        }
      },
      "title": "GPT5Nano",
      "required": [
        "text"
      ]
    }
  }
}

headers = {
    "Content-Type": "application/json",
    "x-api-key": f"{api_key}",
}

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

result = response.json()
print("Queued:", result)

outputs = poll_for_result(result["run_id"])
print("Completed:", outputs)

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