OpenAI o3 is the most advanced reasoning model from OpenAI, purpose-built for handling complex, high-cognition tasks. Launched in April 2025, it delivers exceptional performance in software engineering, mathematics, and scientific problem-solving. The model introduces three levels of reasoning effort—low, medium, and high—allowing users to balance between latency and depth of reasoning based on task complexity. o3 supports essential tools for developers, including function calling, structured outputs, and system-level messaging. With built-in vision capabilities, o3 can interpret and analyze images, making it suitable for multimodal applications. It’s available through Chat Completions API, Assistants API, and Batch API for flexible integration into enterprise and research workflows.
GPT-4.1, launched by OpenAI on April 14, 2025, introduces a 1 million token context window and supports outputs of up to 32,768 tokens per request. It delivers outstanding performance on coding tasks, achieving 54.6% on the SWE-Bench Verified benchmark, and shows a 10.5% improvement over GPT-4o on MultiChallenge for instruction following. The model's knowledge cutoff is set at June 2024. Pricing is $2.00 per million tokens for input and $8.00 per million tokens for output, with a 75% discount applied to cached inputs, making it highly cost-efficient for repeated queries.
| o3 | GPT-4.1 | |
|---|---|---|
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
| $10.00 per million tokens | $2.00 per million tokens |
Pricing Output
| $40.00 per million tokens | $8.00 per million tokens |
MMLU
| 82.9% Source | 90.2% pass@1 Source |
MMLU-Pro
| - | - |
MMMU
| - | 74.8% Source |
HellaSwag
| - | - |
HumanEval
| - | - |
MATH
| - | - |
GPQA
| 83.3% Diamond, no tools Source | 66.3% Diamond Source |
IFEval
| - | - |
SimpleQA
| - | - |
AIME 2024 | 91.6% Source | 48.1% Source |
AIME 2025 | 88.9% Source | - |
Aider Polyglot
| - | - |
LiveCodeBench v5
| - | - |
Global MMLU (Lite)
| - | 87.3% pass@1 Source |
MathVista
| - | - |
Mobile Application |
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