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o3 Pricing

OpenAI · Advanced reasoning model that thinks step-by-step for complex math, science, and

TL;DR
Price: $2.00/1M input · $8.00/1M output
Context: 200K · max 100,000 output
Cost advantage: Up to 70% cheaper than official API
Access: OpenAI-compatible · No credit card · Instant API key

Save up to 70% on o3 API cost

Same model, same quality — pay less per token than the official API. Pay-as-you-go, no credit card required.

$2.00/1M
input token price
INPUT
$2.00
/1M tokens
OUTPUT
$8.00
/1M tokens
CONTEXT
200K

Other OpenAI Models

GPT-5.5
$5.00 / $30.00
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GPT-5.4
$2.50 / $15.00
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GPT-4.1
$2.00 / $8.00
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GPT-4.1 Mini
$0.40 / $1.60
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GPT-4.1 Nano
$0.10 / $0.40
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GPT-4o
$2.50 / $10.00
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GPT-4o Mini
$0.15 / $0.60
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o4-mini
$1.10 / $4.40
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o3-pro
$20.00 / $80.00
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GPT-4 Turbo
$10.00 / $30.00
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Text Embedding 3 Large
$0.13 / $0.13
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Sora 1
$0.50 / $2.00
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o3 Pricing Context

Pricing position within OpenAI

o3 sits in the middle of OpenAI's pricing at $2.00/1M input — 34% below the lineup average ($0.10 cheapest, $20.00 most expensive). 6 siblings cost less, 4 cost more. This mid-tier positioning makes it a sensible default when you're unsure which variant to pick.

When o3 is worth the cost

o3 is deployed for problems that need structured thinking — math derivations, logic puzzles, scientific analysis, and multi-step research synthesis. The reasoning chain adds latency, so reserve it for tasks where a standard chat model produces shallow or incorrect answers. For routine Q&A and summarization, a cheaper sibling model is more cost-effective.

Cost vs sibling models

What makes o3 different from sibling models: compared to GPT-5.5 ($3.00/1M more expensive, 256K vs 200K context (larger)); GPT-5.4 ($0.50/1M more expensive, 256K vs 200K context (larger)); GPT-4.1 ($0.00/1M cheaper, 1M vs 200K context (larger)). Choose o3 when step-by-step reasoning matters more than speed.

Real-world cost scenarios

Real-world deployments: math problem solving, scientific research synthesis, multi-step logical analysis, and structured decision support systems. o3 excels where standard chat models produce shallow answers — the reasoning chain catches edge cases that faster models miss.

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