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Get all the details on o3-2025-04-16, an AI model from OpenAI. This page covers its token limits, pricing structure, key capabilities such as code_interpretation, web_browsing_via_tool, streaming, available API code samples, and performance strengths.
Key Metrics
Input Limit
200K tokens
Output Limit
100K tokens
Input Cost
$10.00/1M
Output Cost
$40.00/1M
Sample API Code
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(model="o3-2025-04-16", messages=[{"role": "user", "content": "Hello world"}])
print(response.choices[0].message.content)
Required Libraries
openai
openai
Benchmarks
Benchmark | Score | Source | Notes |
---|---|---|---|
1409 | OpenLLM Leaderboard | Rank 2 overall | |
1190 | OpenLLM Leaderboard | Rank 7 overall | |
1303 | OpenLLM Leaderboard | Rank 2 overall | |
83.3% | Vellum | Best in Reasoning (GPQA Diamond) | |
91.6% | Vellum | Best in High School Math (AIME 2024) | |
69.1% | Vellum | Best in Agentic Coding (SWE Bench) | |
80.71 | LiveBench | Score for 'o3 High' | |
93.33 | LiveBench | Score for 'o3 High' | |
76.71 | LiveBench | Score for 'o3 High' | |
85.00 | LiveBench | Score for 'o3 High' | |
67.02 | LiveBench | Score for 'o3 High' | |
76.00 | LiveBench | Score for 'o3 High' | |
86.17 | LiveBench | Score for 'o3 High' |
Notes
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.
Supported Data Types
Input Types
text
image
Output Types
text
Strengths & Weaknesses
Exceptional at
math
science
coding
visual reasoning
technical writing
instruction following
multi-step problem solving
multimodal understanding
Good at
general reasoning
well rounded across domains
Additional Information
Latest Update
Apr 16, 2025
Knowledge Cutoff
Jun 1, 2024