OpenAI o4-mini is the newest lightweight model in the o-series, engineered for efficient and capable reasoning across text and visual tasks. Optimized for speed and performance, it excels in code generation and image-based understanding, while maintaining a balance between latency and reasoning depth. The model supports a 200,000-token context window with up to 100,000 output tokens, making it suitable for extended, high-volume interactions. It handles both text and image inputs, producing textual outputs with advanced reasoning capabilities. With its compact architecture and versatile performance, o4-mini is ideal for a wide array of real-world applications demanding fast, cost-effective intelligence.
GPT-4.1 Nano, launched by OpenAI on April 14, 2025, is the company's fastest and most affordable model to date. Designed for low-latency tasks such as classification, autocomplete, and fast inference scenarios, it combines compact architecture with robust capabilities. Despite its size, it supports an impressive 1 million token context window and delivers strong benchmark results, achieving 80.1% on MMLU and 50.3% on GPQA. With a knowledge cutoff of June 2024, GPT-4.1 Nano offers exceptional value at just $0.10 per million input tokens and $0.40 per million output tokens, with a 75% discount applied to cached inputs, making it ideal for high-volume, cost-sensitive deployments.
| o4-mini | GPT-4.1 Nano | |
|---|---|---|
Web Site
| ||
Provider
| ||
Chat
| ||
Release Date
| ||
Modalities
| text images | text images |
API Providers
| OpenAI API | OpenAI API |
Knowledge Cut-off Date
| - | - |
Open Source
| No | No |
Pricing Input
| $1.10 per million tokens | $0.10 per million tokens |
Pricing Output
| $4.40 per million tokens | $0.40 per million tokens |
MMLU
| fort | 80.1% Source |
MMLU-Pro
| - | - |
MMMU
| 81.6% Source | 55.4% Source |
HellaSwag
| - | - |
HumanEval
| 14.28% Source | - |
MATH
| - | - |
GPQA
| 81.4% Source | 50.3% Diamond Source |
IFEval
| - | 74.5% Source |
SimpleQA
| - | - |
AIME 2024 | 93.4% Source | 29.4% Source |
AIME 2025 | 92.7% Source | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | 66.9% Source |
MathVista
| - | 56.2% Image Reasoning Source |
Mobile Application |
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