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OpenAI: GPT-5.2-Codex vs Google: Nano Banana Pro (Gemini 3 Pro Image Preview)

Head-to-head API cost, context, and performance comparison. Synced at 9:50:06 AM.

Executive Summary

When evaluating OpenAI: GPT-5.2-Codex against Google: Nano Banana Pro (Gemini 3 Pro Image Preview), the pricing structure is a key differentiator. Google: Nano Banana Pro (Gemini 3 Pro Image Preview) is approximately 11% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Google: Nano Banana Pro (Gemini 3 Pro Image Preview) leads with a statistical ELO score of 1300. For tasks involving complex logic, coding, or instruction-following, developers might prefer Google: Nano Banana Pro (Gemini 3 Pro Image Preview), provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
OpenAI: GPT-5.2-Codex
Google: Nano Banana Pro (Gemini 3 Pro Image Preview)
Performance (ELO)
1300
1300
Input Cost / 1M
$1.75
$2.00
Output Cost / 1M
$14.00
$12.00
Context Window
400,000 tokens
65,536 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Google: Nano Banana Pro (Gemini 3 Pro Image Preview) wins out aggressively in pricing.

People Also Ask

Is OpenAI: GPT-5.2-Codex cheaper than Google: Nano Banana Pro (Gemini 3 Pro Image Preview)?

No. Google: Nano Banana Pro (Gemini 3 Pro Image Preview) 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-5.2-Codex model has the advantage in memory, offering a massive 400,000 token limit for document ingestion.

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