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Home/Models/OpenAI/GPT-4.1 nano
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GPT-4.1 nano

Masukan:$0.1/M
Keluaran:$0.2/M
Konteks:1.0M
Keluaran Maksimum:1047K
GPT-4.1 nano is an artificial intelligence model provided by OpenAI. gpt-4.1-nano: Features a larger context window—supporting up to 1 million context tokens and capable of better utilizing that context through improved long-context understanding. Has an updated knowledge cutoff time of June 2024. This model supports a maximum context length of 1,047,576 tokens.
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The GPT-4.1 Nano API is OpenAI's most compact and cost-effective language model, designed for high-speed performance and affordability. It supports a context window of up to 1 million tokens, making it ideal for applications requiring efficient processing of large datasets, such as customer support automation, data extraction, and educational tools.

Overview of GPT-4.1 Nano

GPT-4.1 Nano is the smallest and most affordable model in OpenAI's GPT-4.1 lineup, designed for applications requiring low latency and minimal computational resources. Despite its compact size, it maintains robust performance across various tasks, making it suitable for a wide range of applications.

Technical Specifications of GPT-4.1 Nano

Model Architecture and Parameters

While specific architectural details of GPT-4.1 Nano are proprietary, it is understood to be a distilled version of the larger GPT-4.1 models. This distillation process involves reducing the number of parameters and optimizing the model for efficiency without significantly compromising performance.

Context Window

GPT-4.1 Nano supports a context window of up to 1 million tokens, allowing it to handle extensive inputs effectively. This capability is particularly beneficial for tasks involving large datasets or long-form content.

Multimodal Capabilities

The model is designed to process and understand both text and visual inputs, enabling it to perform tasks that require multimodal comprehension. This includes interpreting images alongside textual data, which is essential for applications in fields like education and customer service.

Evolution of GPT-4.1 Nano

GPT-4.1 Nano represents a strategic evolution in OpenAI's model development, focusing on creating efficient models that can operate in environments with limited computational resources. This approach aligns with the growing demand for AI solutions that are both powerful and accessible.

Benchmark Performance of GPT-4.1 Nano

Massive Multitask Language Understanding (MMLU)

GPT-4.1 Nano achieved a score of 80.1% on the MMLU benchmark, demonstrating strong performance in understanding and reasoning across diverse subjects. This score indicates its capability to handle complex language tasks effectively.

Other Benchmarks

For tasks that require low latency, GPT-4.1 nano is the fastest and lowest-cost model in the GPT-4.1 family. With a 1 million token context window, it achieves excellent performance in a small size, 50.3% in the GPQA test, and 9.8% in the Aider multi-language coding test, even higher than GPT-4o mini. It is well suited for tasks such as classification or auto-completion.

Technical Indicators of GPT-4.1 Nano

Latency and Throughput

GPT-4.1 Nano is optimized for low latency, ensuring quick response times in real-time applications. Its high throughput allows it to process large volumes of data efficiently, which is crucial for applications like chatbots and automated customer service.

Cost Efficiency

The model is designed to be cost-effective, reducing the computational expenses associated with deploying AI solutions. This makes it an attractive option for businesses and developers looking to implement AI without incurring high costs.

Application Scenarios

Edge Computing

Due to its compact size and efficiency, GPT-4.1 Nano is ideal for edge computing applications, where resources are limited, and low latency is critical. This includes use cases in IoT devices and mobile applications.

Customer Service Automation

The model's ability to understand and generate human-like text makes it suitable for automating customer service interactions, providing quick and accurate responses to user inquiries.

Educational Tools

GPT-4.1 Nano can be integrated into educational platforms to provide personalized learning experiences, answer student queries, and assist in content creation.

Healthcare Support

In healthcare, the model can assist in preliminary patient interactions, providing information and answering common questions, thereby reducing the workload on medical professionals.

Harga untuk GPT-4.1 nano

Jelajahi harga kompetitif untuk GPT-4.1 nano, dirancang untuk berbagai anggaran dan kebutuhan penggunaan. Paket fleksibel kami memastikan Anda hanya membayar untuk apa yang Anda gunakan, memudahkan untuk meningkatkan skala seiring berkembangnya kebutuhan Anda. Temukan bagaimana GPT-4.1 nano dapat meningkatkan proyek Anda sambil menjaga biaya tetap terkendali.
Harga Comet (USD / M Tokens)Harga Resmi (USD / M Tokens)Diskon
Masukan:$0.1/M
Keluaran:$0.2/M
Masukan:$0.125/M
Keluaran:$0.25/M
-20%

Kode contoh dan API untuk GPT-4.1 nano

The GPT-4.1 Nano API is OpenAI's most compact and cost-effective language model, designed for high-speed performance and affordability. It supports a context window of up to 1 million tokens, making it ideal for applications requiring efficient processing of large datasets, such as customer support automation, data extraction, and educational tools.
Python
JavaScript
Curl
from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)
response = client.responses.create(
    model="gpt-4.1-nano-2025-04-14", input="Tell me a three sentence bedtime story about a unicorn."
)

print(response)

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)
response = client.responses.create(
    model="gpt-4.1-nano-2025-04-14", input="Tell me a three sentence bedtime story about a unicorn."
)

print(response)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const api_key = process.env.COMETAPI_KEY;
const base_url = "https://api.cometapi.com/v1";

const openai = new OpenAI({
  apiKey: api_key,
  baseURL: base_url,
});

const response = await openai.responses.create({
  model: "gpt-4.1-nano-2025-04-14",
  input: "Tell me a three sentence bedtime story about a unicorn.",
});

console.log(response);

Curl Code Example

curl https://api.cometapi.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "gpt-4.1-nano-2025-04-14",
    "input": "Tell me a three sentence bedtime story about a unicorn."
  }'

Versi GPT-4.1 nano

Alasan GPT-4.1 nano memiliki beberapa _snapshot_ mungkin mencakup faktor-faktor potensial seperti variasi keluaran setelah pembaruan yang memerlukan _snapshot_ lama untuk konsistensi, memberikan masa transisi bagi pengembang untuk beradaptasi dan bermigrasi, serta _snapshot_ berbeda yang sesuai dengan _endpoint_ global atau regional untuk mengoptimalkan pengalaman pengguna. Untuk perbedaan detail antar versi, silakan merujuk ke dokumentasi resmi.
version
gpt-4.1-nano
gpt-4.1-nano-2025-04-14