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

GPT-4 Turbo

OpenAI

GPT-4 Turbo is a language model developed by OpenAI. It achieves strong performance with an average score of 78.1% across 6 benchmarks. It excels particularly in MGSM (88.5%), HumanEval (87.1%), MMLU (86.5%). It supports a 132K 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

GPT-4 Turbo

OpenAI

2024-04-09

Google

Gemini 2.5 Pro

Google

2025-05-20

1 year newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.5 Pro

$28.75 cheaper
Input:$1.25
Output:$10.00
OpenAI

GPT-4 Turbo

Input:$10.00
Output:$30.00

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
OpenAI

GPT-4 Turbo

Max Context:132.1K

Average performance across 1 common benchmarks

Google

Gemini 2.5 Pro

+35.0%
Average Score:83.0%
OpenAI

GPT-4 Turbo

Average Score:48.0%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

code
70.6%
general
69.4%
OpenAI

GPT-4 Turbo

code
+16.5%
87.1%
general
+4.1%
73.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-4 Turbo

2023-12-31

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

GPT-4 Turbo

2 providers

Azure

Throughput: 97 tok/s
Latency: 0.6ms

OpenAI

Throughput: 100 tok/s
Latency: 0.5ms
Google

Gemini 2.5 Pro

+35.0%
Avg Score:83.0%
Providers:1
OpenAI

GPT-4 Turbo

Avg Score:48.0%
Providers:2