GPT-4.1 Mini API

openai/gpt-4.1-mini-2025-04-14
Balanced AI with million-token context providing performance at reduced cost.
Context
1M tokens
Input
$0.52 / 1M tokens
Output
$2.08 / 1M tokens
Released
Aug 7, 2025

Overview

GPT-4.1 Mini Description

GPT-4.1 Mini is OpenAI's mid-tier model in the GPT-4.1 family, designed to provide a balance between high performance and cost efficiency. It delivers capabilities comparable to the full GPT-4.1 model at significantly lower cost, making it ideal for applications where budget considerations are important but performance can't be compromised. The model excels at coding tasks, instruction following, and processing long contextual information, offering enterprises and developers an efficient solution for a wide range of AI applications.

Technical Specifications

Context Window and Token Capacity

GPT-4.1 Mini processes input contexts of up to 1,047,576 tokens (approximately 750,000 words), matching the full GPT-4.1 model's capacity. The model generates outputs of up to 32,768 tokens in a single response. All training data for GPT-4.1 Mini extends to May 31, 2024, which serves as its knowledge cutoff date.

API Pricing

Input tokens $0.52 per million tokens

Output tokens $2.08 per million tokens

Performance Benchmarks

GPT-4.1 Mini demonstrates strong performance across multiple benchmarks, offering capabilities that in many cases match or come close to the full GPT-4.1 model:

  • Visual Reasoning (MathVista): 73.1% accuracy (slightly outperforming the full GPT-4.1 model)
  • Instruction Following: Near-parity with GPT-4.1 on instruction benchmarks
  • Long Context Processing: Full 1M token context handling with maintained coherence
  • Multi-document Analysis: Strong performance on legal and financial document analysis

Key Capabilities

Programming and Software Development

GPT-4.1 Mini delivers strong coding capabilities with minimal performance tradeoff compared to the full model. It provides effective code refactoring and debugging features for a wide range of programming languages. The model follows programming best practices with high reliability across multiple frameworks and languages. It generates optimized code with fewer extraneous edits compared to previous models. GPT-4.1 Mini supports practical development workflows including repository analysis and pull request generation. The system performs well across standard coding benchmarks, particularly for everyday development tasks.

Long Context Processing

GPT-4.1 Mini processes and reasons over documents containing up to 1 million tokens with strong coherence throughout. The model retrieves specific information from large documents effectively even when key data is deeply embedded. It analyzes complex codebases and multiple documents with improved accuracy over previous generations. GPT-4.1 Mini handles multi-document analysis with strong performance for research and business applications. Like the full model, it is optimized for XML-style delimiters to enhance structure in long-context inputs.

Balanced Performance and Efficiency

GPT-4.1 Mini offers 83% lower cost than GPT-4o while outperforming it on many benchmarks. The model achieves enhanced latency and response speed compared to more expensive models. It balances computational efficiency with strong performance across diverse tasks. GPT-4.1 Mini provides significantly higher quality results than comparably priced models from previous generations. The system delivers optimal resource utilization for high-volume, production-scale deployments.

Visual Understanding

GPT-4.1 Mini demonstrates exceptional visual reasoning capabilities, even outperforming the full model on some benchmarks. It processes images in combination with text for improved multimodal understanding. The model interprets charts, graphs, and visual data with high accuracy. It provides enhanced document parsing and visual content analysis. GPT-4.1 Mini offers cost-effective image understanding for applications that combine text and visual elements.

Integration and Availability

GPT-4.1 Mini is available through AIML's API services for developers and organizations. OpenAI has planned a gradual integration of GPT-4.1 Mini features into the ChatGPT interface over time. The system provides comprehensive support for tool calling and complex workflows with enhanced reliability and efficiency.

API references - Documentation

Limitations and Considerations

GPT-4.1 Mini experiences some performance degradation with extremely large inputs, though less pronounced than many comparable models. The model interprets instructions more literally than GPT-4o, requiring more specific and explicit prompts for optimal results. It sacrifices some capabilities of the full GPT-4.1 model in exchange for improved speed and lower cost. GPT-4.1 Mini maintains most strengths of the full model while being optimized for broader deployment scenarios.

Optimal Use Cases

GPT-4.1 Mini excels in moderately complex software development projects requiring a balance of performance and cost. The model performs efficiently for document analysis and information extraction across diverse industries. It provides high-quality responses for customer-facing applications without premium model costs. GPT-4.1 Mini supports multi-document question answering with strong context retention. The system delivers superior code base understanding for legacy system modernization. It enables efficient API and integration development with structured outputs and accurate documentation.

Comparison with Other Models

GPT-4.1 Mini matches or exceeds GPT-4o performance while costing 83% less. It provides stronger coding capabilities than GPT-4.5 on many benchmarks at a fraction of the price. The model offers a performance upgrade over GPT-4o mini with minimal latency impact. GPT-4.1 Mini delivers capabilities that were previously only available in the most expensive models. It outperforms competing mid-tier models from other providers on key development benchmarks.

Summary

GPT-4.1 Mini represents an optimal balance between capability and cost within OpenAI's model lineup. It delivers premium model features at a significantly reduced price point, making advanced AI capabilities accessible to a broader range of applications and organizations. With its strong performance across coding, document processing, and instruction following tasks, GPT-4.1 Mini offers an efficient solution for most enterprise and development needs without the premium cost of the full model.

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Uptime and performance

  • Uptime (24h): 67.0%
  • Uptime (7d): 95.0%
  • Availability (24h): 20.0%
  • Error rate (24h): 80.0%
  • End-to-end latency (24h median): 567ms
  • Throughput (24h median): 13.6 tok/s

Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.

Use cases

  • Software development and AI pair programming
  • Enterprise meeting transcription and analysis
  • Image-based report generation and visual data interpretation
  • Advanced customer support and knowledge management
  • Automated workflows requiring long-context understanding and complex reasoning

How to use GPT-4.1 Mini API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to openai/gpt-4.1-mini-2025-04-14.
import requests

r = requests.post(
    "https://api.aimlapi.com/v1/chat/completions",
    headers={"Authorization": "Bearer " + AIMLAPI_KEY},
    json={
      "model": "openai/gpt-4.1-mini-2025-04-14",
      "messages": [
        {
          "role": "user",
          "content": "Hello!"
        }
      ]
    },
)
print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "openai/gpt-4.1-mini-2025-04-14",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }),
});
console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"openai/gpt-4.1-mini-2025-04-14","messages":[{"role":"user","content":"Hello!"}]}'

OpenAI-compatible — swap the base URL and it works with your existing SDK.

GPT-4.1 Mini API Pricing

TypePrice
Input
$0.52 / 1M tokens
Output
$2.08 / 1M tokens
Cached input
$0.13 / 1M tokens

GPT-4.1 Mini Benchmarks

BenchmarkScoreWhat it measuresSourceRetrieved
GPQA Diamond
65%
Google-proof graduate science questions (hardest subset)SourceJuly 12, 2026
SWE-bench Verified
23.6%
Resolving verified real GitHub issuesSourceJuly 12, 2026
Intelligence
10.2
Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial AnalysisSourceSeptember 12, 2026
Coding
20.2
Composite score across standardised coding evaluations, measured independently by Artificial AnalysisSourceSeptember 12, 2026
Math
46.3
Composite score across standardised mathematics evaluations, measured independently by Artificial AnalysisSourceSeptember 12, 2026

GPT-4.1 Mini vs other models

ModelInputOutputContextBest for
GPT-4.1 Mini
This page
$0.52 / 1M tokens
$2.08 / 1M tokens
1M tokens
Coding + agents
$6.5 / 1M tokens
$39 / 1M tokens
1M tokens
Reasoning + agents
$2.6 / 1M tokens
$13 / 1M tokens
1M tokens
Balanced coding + agents
$3.9 / 1M tokens
$19.5 / 1M tokens
1M tokens
Long-context, multimodal & agentic workflows
$1.95 / 1M tokens
$11.7 / 1M tokens
1M tokens
Reasoning + agents

Frequently asked questions

GPT-4.1 Mini has a 1,000,000 tokens context window.

GPT-4.1 Mini takes image, text as input and returns text.

Use openai/gpt-4.1-mini-2025-04-14 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.

GPT-4.1 Mini became available on August 7, 2025.

GPT-4.1 Mini is priced at input $0.52 / 1M tokens, output $2.08 / 1M tokens, cached input $0.13 / 1M tokens.

Yes, GPT-4.1 Mini can stream responses as they are generated.

Yes, GPT-4.1 Mini accepts image input alongside text.

GPT-4.1 Mini was built by OpenAI.

Yes, it supports function calling, tools, and parallel tool calls.

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