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OpenAI: GPT-5.1-Codex-Max vs Google: Gemini 2.5 Pro

Head-to-head API cost, context, and performance comparison. Synced at 9:49:12 AM.

Executive Summary

When evaluating OpenAI: GPT-5.1-Codex-Max against Google: Gemini 2.5 Pro, the pricing structure is a key differentiator. Both models are remarkably similar in API costs.

However, when looking at raw reasoning capabilities, Google: Gemini 2.5 Pro leads with a statistical ELO score of 1300. For tasks involving complex logic, coding, or instruction-following, developers might prefer Google: Gemini 2.5 Pro, provided their budget allows for the API burn rate.

Raw Technical comparison

Metric
OpenAI: GPT-5.1-Codex-Max
Google: Gemini 2.5 Pro
Performance (ELO)
1300
1300
Input Cost / 1M
$1.25
$1.25
Output Cost / 1M
$10.00
$10.00
Context Window
400,000 tokens
1,048,576 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Tie wins out aggressively in pricing.

People Also Ask

Is OpenAI: GPT-5.1-Codex-Max cheaper than Google: Gemini 2.5 Pro?

No. Google: Gemini 2.5 Pro is the more cost-effective model, operating at a lower price point per 1 million tokens.

Which model has the larger context window?

The Google: Gemini 2.5 Pro model has the advantage in memory, offering a massive 1,048,576 token limit for document ingestion.

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