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OpenAI: GPT-5.1-Codex vs Google: Nano Banana Pro (Gemini 3 Pro Image)

Head-to-head API cost, context, and performance comparison. Synced at 4:36:05 PM.

Executive Summary

When evaluating OpenAI: GPT-5.1-Codex against Google: Nano Banana Pro (Gemini 3 Pro Image), the pricing structure is a key differentiator. OpenAI: GPT-5.1-Codex is approximately 20% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, OpenAI: GPT-5.1-Codex leads with a statistical ELO score of 1481. For tasks involving complex logic, coding, or instruction-following, developers might prefer OpenAI: GPT-5.1-Codex, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
OpenAI: GPT-5.1-Codex
Google: Nano Banana Pro (Gemini 3 Pro Image)
Performance (ELO)
1481
1480
Input Cost / 1M
$1.25
$2.00
Output Cost / 1M
$10.00
$12.00
Context Window
400,000 tokens
131,072 tokens

Verdict

If you are looking for pure performance and capability, OpenAI: GPT-5.1-Codex is statistically superior. However, if API burn rate is the primary concern, OpenAI: GPT-5.1-Codex wins out aggressively in pricing.

People Also Ask

Is OpenAI: GPT-5.1-Codex cheaper than Google: Nano Banana Pro (Gemini 3 Pro Image)?

Yes. OpenAI: GPT-5.1-Codex is cheaper for both input and output generation compared to Google: Nano Banana Pro (Gemini 3 Pro Image). Exploring alternatives often yields cost reductions.

Which model has the larger context window?

The OpenAI: GPT-5.1-Codex model has the advantage in memory, offering a massive 400,000 token limit for document ingestion.

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