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OpenAI: GPT-5.3-Codex vs OpenAI: o3

Head-to-head API cost, context, and performance comparison. Synced at 9:50:09 AM.

Executive Summary

When evaluating OpenAI: GPT-5.3-Codex against OpenAI: o3, the pricing structure is a key differentiator. OpenAI: o3 is approximately 37% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, OpenAI: GPT-5.3-Codex leads with a statistical ELO score of 1410. For tasks involving complex logic, coding, or instruction-following, developers might prefer OpenAI: GPT-5.3-Codex, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
OpenAI: GPT-5.3-Codex
OpenAI: o3
Performance (ELO)
1410
1300
Input Cost / 1M
$1.75
$2.00
Output Cost / 1M
$14.00
$8.00
Context Window
400,000 tokens
200,000 tokens

Verdict

If you are looking for pure performance and capability, OpenAI: GPT-5.3-Codex is statistically superior. However, if API burn rate is the primary concern, OpenAI: o3 wins out aggressively in pricing.

People Also Ask

Is OpenAI: GPT-5.3-Codex cheaper than OpenAI: o3?

No. OpenAI: o3 is the more cost-effective model, operating at a lower price point per 1 million tokens.

Which model has the larger context window?

The OpenAI: GPT-5.3-Codex model has the advantage in memory, offering a massive 400,000 token limit for document ingestion.

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