OpenAI GPT 4.1 API - AI Language Models Tool

Overview

OpenAI GPT‑4.1 is a flagship large language model family released as an API-grade successor to earlier GPT‑4 variants. It emphasizes production-readiness for real-world tasks: instruction-following, code generation, function/tool calling, and very-long-context document understanding. The model supports an unusually large context window (about 1,047,576 tokens) and is exposed via both the Responses and Chat Completions endpoints, plus Realtime and Batch workflows for low-latency and high-throughput use cases (OpenAI platform docs). GPT‑4.1 is offered alongside smaller siblings (GPT‑4.1‑mini and nano) to balance cost and speed across workloads. Since launch the model has been highlighted for improved coding performance and faster response times versus prior OpenAI models; independent reporting cited a 55% score on SWE‑Bench for coding workloads, and OpenAI’s docs and release notes emphasize better instruction following, structured outputs, and tool calling support (Wired; OpenAI docs). Community feedback has been mixed: many developers praise the long-context handling and speed, while some users reported regressions for specific coding or stylistic workflows. OpenAI announced that GPT‑4.1 (and some related models) were retired from ChatGPT on February 13, 2026, though, per the company, API access was initially unaffected—developers should confirm current availability and migration guidance on OpenAI’s site before deploying new production workloads (OpenAI blog/help).

Key Features

• Up to ~1,047,576-token context window for multi-document and long‑conversation workflows.
• Native support for Responses, Chat Completions, Realtime, and Batch endpoints.
• Function/tool calling, structured outputs, and streaming responses for agentic apps.
• Fine‑tuning and snapshot/locking to stabilize behavior for production deployments.
• Optimized coding and instruction following — reported gains on code‑generation benchmarks.

Example Usage

Example (python):

from openai import OpenAI

# Requires openai-python package and OPENAI_API_KEY set in env
client = OpenAI()

# Simple Responses API call using gpt-4.1
resp = client.responses.create(
    model="gpt-4.1",
    input=[
        {"role": "system", "content": "You are a concise technical assistant."},
        {"role": "user", "content": "Summarize the main risks of using a 1M-token context model in production."}
    ],
    # optional: stream=True for streaming, or background=True for async batch-style jobs
)

print(resp.output_text)

Pricing

OpenAI publishes per‑token pricing for GPT‑4.1 on its platform pages. Example on the model page shows input ≈ $2 / 1M tokens and output ≈ $8 / 1M tokens for long‑context usage; OpenAI’s pricing page also lists fine‑tuning and training rates (e.g., fine‑tuning input $3 /1M, output $12 /1M, training $25 /1M). Confirm current, region‑specific, and tiered pricing on OpenAI’s official pricing pages before budgeting or deployment. (Sources: OpenAI model docs and pricing page.)

Benchmarks

Context window: 1,047,576 tokens (≈1M token context) (Source: https://platform.openai.com/docs/models/gpt-4.1)

SWE‑Bench (coding): 55% (reported score on SWE‑Bench) (Source: https://www.wired.com/story/openai-announces-4-1-ai-model-coding)

API token pricing (per 1M tokens, example rates): Input ≈ $2 / 1M tokens; Output ≈ $8 / 1M tokens (model-specific pricing shown in model docs) (Source: https://platform.openai.com/docs/models/gpt-4.1)

Fine-tuning (example from OpenAI pricing page): Fine-tuning input $3 /1M, output $12 /1M, training $25 /1M (OpenAI pricing page) (Source: https://openai.com/api/pricing//)

Key Information

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