Model Cost Profile

OpenAI: o3

Developer: openai

Pricing updated Mar 11, 2026

Input rank: #283Output rank: #272

Live Pricing

Input: $2.00

Output: $8.00

Pricing via OpenRouter API ยท Last synced Mar 11, 2026 ยท MMLU score via public benchmark data

OpenAI's o3 model features an extensive context window of 200,000 tokens, making it ideal for applications requiring deep context retention, such as long-form content generation and complex data analysis. Teams leveraging the o3 API can anticipate input costs of $2.00 per 1 million tokens and output costs of $8.00 per 1 million tokens, allowing for scalable budgeting based on usage patterns. This pricing structure supports diverse use cases, from chatbots to large-scale document processing, enabling organizations to optimize their operational efficiency.

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Context Window

200,000

Tokens

Input Price / 1M

$2.00

Prompt tokens

Output Price / 1M

$8.00

Completion tokens

Intelligence (MMLU)

85.3

Massive Multitask Language Understanding

Benchmark Scores

Standardized evaluation scores for OpenAI: o3.

BenchmarkScoreRankSource
GPQA82.7#13 of 118artificial_analysis
MMLU85.3#11 of 121artificial_analysis

Price History

OpenAI: o3 Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$2.00$5.00$8.00Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$2.00

Current Output / 1M

$8.00

Cheaper Alternatives to Compare

Quick links for cost-down decisions before production rollout.

FAQ

Common pricing and benchmark questions for OpenAI: o3.

How much does OpenAI: o3 cost per 1M input tokens?

OpenAI: o3 input pricing is $2.00 per 1M tokens based on the latest synced provider data.

How much does OpenAI: o3 cost per 1M output tokens?

OpenAI: o3 output pricing is $8.00 per 1M tokens based on the latest synced provider data.

What context window does OpenAI: o3 support?

OpenAI: o3 supports a context window of 200,000 tokens.

How can I compare OpenAI: o3 with cheaper alternatives?

Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.