OpenAI GPT 4.1 API - AI Language Models Tool

Overview

OpenAI GPT-4.1 is a flagship large language model released for the API with a primary focus on real-world production workloads: large-context understanding, improved coding, stronger instruction following, and higher formatting fidelity. GPT-4.1 and its smaller variants (mini, nano) are trained and validated to handle up to ~1,047,576 tokens of context, and were released with a June 1, 2024 knowledge cutoff. ([platform.openai.com](https://platform.openai.com/docs/models/gpt-4.1?utm_source=openai)) The model is positioned for tasks that require processing very large inputs (entire codebases, long legal/financial documents, or multi-file agent workflows) and for building agentic systems that call tools reliably. Benchmarks published by OpenAI highlight substantial gains in coding and long-context multimodal evaluation (for example, a 54.6% score on SWE-bench Verified and 72.0% on a long Video-MME category), and OpenAI reports optimized throughput, lower latency, and improved cost-efficiency versus earlier research previews. GPT-4.1 is available via the OpenAI API only and supports production features such as prompt caching and the Batch API. ([openai.com](https://openai.com/index/gpt-4-1/?utm_source=openai))

Key Features

• Up to ~1,047,576 token context window for multi-file and long-document tasks.
• Supports up to 32,768 output tokens for very long generated outputs.
• Improved coding: higher pass rates and more reliable diff/patch formatting.
• Stronger instruction-following and format compliance for structured outputs.
• Optimized for agentic workflows and reliable tool calling.
• Lower latency and cost-efficiency versus prior GPT-4.5 preview models.

Example Usage

Example (python):

from openai import OpenAI

# Install the official OpenAI Python client (openai>=1.0)
# pip install openai

client = OpenAI()

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Summarize the key points from the following long document..."}
]

# Create a chat completion with GPT-4.1
resp = client.chat.completions.create(
    model="gpt-4.1",
    messages=messages,
    # Control length of the assistant response (server-enforced limits apply)
    max_tokens=1024,
    temperature=0.2,
)

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

Pricing

OpenAI publishes both inference and fine-tuning prices for GPT-4.1. In the API docs, GPT-4.1 inference is listed at approximately $2 (input) / $8 (output) per 1M tokens (displayed as $2•$8 in model docs), and fine-tuning prices are shown as $3.00 / 1M input tokens, $0.75 / 1M cached input, $12.00 / 1M output, and $25.00 / 1M training tokens. (Refer to OpenAI’s model page and pricing page for the canonical, up-to-date billing details.) ([platform.openai.com](https://platform.openai.com/docs/models/gpt-4.1?utm_source=openai))

Benchmarks

SWE-bench Verified (coding): 54.6% (Source: https://openai.com/index/gpt-4-1/)

MultiChallenge (instruction following): 38.3% (Source: https://openai.com/index/gpt-4-1/)

Video-MME (long multimodal QA, no-subtitles): 72.0% (Source: https://openai.com/index/gpt-4-1/)

IFEval (format compliance): 87.4% (Source: https://replicate.com/openai/gpt-4.1)

Graphwalks (multi-hop reasoning): 62% (Source: https://replicate.com/openai/gpt-4.1)

Key Information

• Category: Language Models
• Type: AI Language Models Tool