Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 2.5 Pro

Google

Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 67.1% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). The model shows particular specialization in vision tasks with an average performance of 82.2%. With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

OpenAI

o1-preview

OpenAI

o1-preview is a language model developed by OpenAI. It achieves strong performance with an average score of 64.8% across 8 benchmarks. It excels particularly in MGSM (90.8%), MMLU (90.8%), MATH (85.5%). The model shows particular specialization in math tasks with an average performance of 88.1%. It supports a 161K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents OpenAI's latest advancement in AI technology.

OpenAI

o1-preview

OpenAI

2024-09-12

Google

Gemini 2.5 Pro

Google

2025-05-20

8 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.5 Pro

$63.75 cheaper
Input:$1.25
Output:$10.00
OpenAI

o1-preview

Input:$15.00
Output:$60.00

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
OpenAI

o1-preview

Max Context:160.8K

Average performance across 4 common benchmarks

Google

Gemini 2.5 Pro

+12.5%
Average Score:62.3%
OpenAI

o1-preview

Average Score:49.8%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

general
+11.4%
69.4%
OpenAI

o1-preview

general
58.0%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.5 Pro

2025-01-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
OpenAI

o1-preview

2 providers

Azure

Throughput: 16 tok/s
Latency: 0.54ms

OpenAI

Throughput: 66 tok/s
Latency: 16.2ms
Google

Gemini 2.5 Pro

+12.5%
Avg Score:62.3%
Providers:1
OpenAI

o1-preview

Avg Score:49.8%
Providers:2