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GPT-4.1 mini vs GPT-5 Mini

Compare GPT-4.1 mini and GPT-5 Mini side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, OCR, Object Detection, and Classification.

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OpenAIGPT-4.1 mini

GPT-4.1 mini is deprecated and can no longer be run. Details and evals are still available on its model page.

OpenAIGPT-5 Mini
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GPT-4.1 mini vs GPT-5 Mini Comparison Table

Evals updated August 14, 2026Pricing updated August 16, 2026

PropertyGPT-4.1 miniGPT-5 Mini
OrganizationOpenAIOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateApr 2025Aug 2025
Context Window1.0M400K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.400$0.250
Output $/1M$1.60$2.00
Vision Tasks
CaptioningDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision

GPT-4.1 mini vs GPT-5 Mini: Overview

GPT-4.1 mini

GPT-4.1 mini, released by OpenAI in April 2025, is a smaller, faster, and cheaper variant of GPT-4.1 designed for high-throughput and cost-sensitive applications. It is multimodal, handling both text and images, and inherits the full model’s strengths in coding, structured outputs, and long-context reasoning. With support for up to 1 million tokens, it enables reliable processing of extended documents, multi-file codebases, and lengthy conversations while keeping latency low.

GPT-4.1 mini offers an efficient alternative to GPT-4.1 and replaced GPT-4o mini as the default ChatGPT model in May 2025. Despite being smaller, it matches or outperforms GPT-4o on several benchmarks, particularly for instruction following and real-world coding tasks. Ideal use cases include large-scale conversational systems, affordable developer tools, document analysis, and interactive assistants where speed and cost are critical.

GPT-5 Mini

GPT-5 Mini, released by OpenAI on August 7, 2025, is a mid-tier variant of the GPT-5 family that balances cost, speed, and capability. It is multimodal, supporting both text and image inputs, and offers a substantial input context window of ~400,000 tokens with output lengths up to ~128,000 tokens. While less powerful than the full GPT-5, it inherits its safety tuning, instruction-following improvements, and multimodal reasoning, making it a practical choice for developers who need large context handling without the expense of premium models.

GPT-5 Mini is optimized for affordability while retaining strong reasoning performance. Benchmarks show it outperforming earlier models such as GPT-4o on many multimodal and medical VQA tasks, though it lags behind GPT-5 on the most complex problems. Ideal use cases include prototyping, scalable content generation, document analysis, and mid-range reasoning tasks where efficiency and context capacity matter more than top-tier accuracy.