OpenAI
o3legacy
Chain-of-thought reasoning model, a former math and code benchmark leader.
Intelligence
32.0 #496
Top 65% tier
Output Speed
90 t/s
ITL 11.1 ms/tok
Blended price (3:1)
$4.375 /1M
In $2.5/M · Out $10/M
Context
200K
≈ 500 A4 pages · max out 16,384
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
o3
Claude Mythos Preview (#1)
Average (68)
Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.
Strengths & Trade-offs
Where it wins
- Cheap prompt-cache reads at $0.25/1M
- Reasoning mode with adjustable effort levels
Trade-offs to watch
- Legacy tier — a newer successor is available
- Architecture and weights undisclosed — API access only
Killer Use Cases
Whole-repo analysis
Single-pass ingestion of large codebases, contracts or research corpora.
Vision & document OCR
Extracts structure from scans, charts, screenshots and mixed-media inputs.
Developer Quickstart & API
Set
OPENAI_API_KEY first — get an API keycurl https://api.openai.com/v1/responses \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "o3",
"input": "Refactor this function for O(n) time and explain the change."
}'from openai import OpenAI
client = OpenAI() # reads OPENAI_API_KEY
resp = client.responses.create(
model="o3",
input="Refactor this function for O(n) time and explain the change.",
)
print(resp.output_text)const res = await fetch("https://api.openai.com/v1/responses", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
"content-type": "application/json",
},
body: JSON.stringify({ model: "o3", input: "Refactor this function for O(n) time and explain the change." }),
});
console.log((await res.json()).output_text);Official Resources & Links
API deployment
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Scores by Source
Category Scores
Benchmark Results
Live Specs & Architecture
Under the hood
- Switchable reasoning effort — trading latency and tokens for accuracy on hard problems.
- Prompt caching supported — cached input reads at $0.25/1M tokens.
Release date
Apr 15, 2025
Parameters
Not disclosed
License
Proprietary
Context Window
200,000 tokens
Max Output
16,384 tokens
Modalities
text + image
Cache Pricing
read $0.25 · write $3.125 /1M
Reasoning
Effort levels
Input Price
$2.5/M
Output Price
$10/M
Output Speed
90 t/s
Time to First Token
—
Data Updated
Aug 5, 2026
Estimated monthly bill
Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...
Cite & embed
GitHub Markdown badge
Loading badge markdown...BibTeX
@misc{llmpodium2026o3,
title = {Benchmark Analysis and Intelligence Evaluation of o3},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/o3}
}Embed Score Badge
Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.
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