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OpenAI: o3 Mini High (batch) vs Google: Gemini 2.5 Pro (batch)

Head-to-head API cost, context, and performance comparison. Synced at 3:21:59 PM.

Executive Summary

When evaluating OpenAI: o3 Mini High (batch) against Google: Gemini 2.5 Pro (batch), the pricing structure is a key differentiator. OpenAI: o3 Mini High (batch) is approximately 51% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, OpenAI: o3 Mini High (batch) leads with a statistical ELO score of 1503. For tasks involving complex logic, coding, or instruction-following, developers might prefer OpenAI: o3 Mini High (batch), provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
OpenAI: o3 Mini High (batch)
Google: Gemini 2.5 Pro (batch)
Performance (ELO)
1503
1499
Input Cost / 1M
$0.55
$0.63
Output Cost / 1M
$2.20
$5.00
Context Window
200,000 tokens
1,048,576 tokens

Verdict

If you are looking for pure performance and capability, OpenAI: o3 Mini High (batch) is statistically superior. However, if API burn rate is the primary concern, OpenAI: o3 Mini High (batch) wins out aggressively in pricing.

People Also Ask

Is OpenAI: o3 Mini High (batch) cheaper than Google: Gemini 2.5 Pro (batch)?

Yes. OpenAI: o3 Mini High (batch) is cheaper for both input and output generation compared to Google: Gemini 2.5 Pro (batch). Exploring alternatives often yields cost reductions.

Which model has the larger context window?

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

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