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-4.1 nano

OpenAI

GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). 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 OpenAI's latest advancement in AI technology.

OpenAI

GPT-4.1 nano

OpenAI

2025-04-14

Google

Gemini 2.5 Pro

Google

2025-05-20

1 month newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.5 Pro

Input:$1.25
Output:$10.00
OpenAI

GPT-4.1 nano

$10.75 cheaper
Input:$0.10
Output:$0.40

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
OpenAI

GPT-4.1 nano

Max Context:1.1M

Average performance across 5 common benchmarks

Google

Gemini 2.5 Pro

+50.5%
Average Score:80.8%
OpenAI

GPT-4.1 nano

Average Score:30.2%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

vision
+26.8%
82.2%
code
70.6%
general
+37.0%
69.4%
OpenAI

GPT-4.1 nano

vision
55.4%
code
+3.9%
74.5%
general
32.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-4.1 nano

2024-05-31

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-4.1 nano

1 providers

OpenAI

Throughput: 200 tok/s
Latency: 2ms
Google

Gemini 2.5 Pro

+50.5%
Avg Score:80.8%
Providers:1
OpenAI

GPT-4.1 nano

Avg Score:30.2%
Providers:1