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Google: Nano Banana 2 (Gemini 3.1 Flash Image) vs OpenAI: GPT-5.1-Codex-Max

Head-to-head API cost, context, and performance comparison. Synced at 6:50:07 AM.

Executive Summary

When evaluating Google: Nano Banana 2 (Gemini 3.1 Flash Image) against OpenAI: GPT-5.1-Codex-Max, the pricing structure is a key differentiator. Google: Nano Banana 2 (Gemini 3.1 Flash Image) is approximately 69% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, OpenAI: GPT-5.1-Codex-Max leads with a statistical ELO score of 1506. For tasks involving complex logic, coding, or instruction-following, developers might prefer OpenAI: GPT-5.1-Codex-Max, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Google: Nano Banana 2 (Gemini 3.1 Flash Image)
OpenAI: GPT-5.1-Codex-Max
Performance (ELO)
1506
1506
Input Cost / 1M
$0.50
$1.25
Output Cost / 1M
$3.00
$10.00
Context Window
131,072 tokens
400,000 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 2 (Gemini 3.1 Flash Image) wins out aggressively in pricing.

People Also Ask

Is Google: Nano Banana 2 (Gemini 3.1 Flash Image) cheaper than OpenAI: GPT-5.1-Codex-Max?

Yes. Google: Nano Banana 2 (Gemini 3.1 Flash Image) is cheaper for both input and output generation compared to OpenAI: GPT-5.1-Codex-Max. Exploring alternatives often yields cost reductions.

Which model has the larger context window?

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

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