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.

IBM

Granite 3.3 8B Instruct

IBM

Granite 3.3 8B Instruct is a multimodal language model developed by IBM. It achieves strong performance with an average score of 69.8% across 14 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). The model shows particular specialization in code tasks with an average performance of 78.3%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents IBM's latest advancement in AI technology.

IBM

Granite 3.3 8B Instruct

IBM

2025-04-16

Google

Gemini 2.5 Pro

Google

2025-05-20

1 month newer

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
IBM

Granite 3.3 8B Instruct

Max Context:-
Parameters:8.0B

Average performance across 1 common benchmarks

Google

Gemini 2.5 Pro

+10.8%
Average Score:92.0%
IBM

Granite 3.3 8B Instruct

Average Score:81.2%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

code
70.6%
general
+5.5%
69.4%
IBM

Granite 3.3 8B Instruct

code
+7.7%
78.3%
general
63.9%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Granite 3.3 8B Instruct

2024-04-01

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
IBM

Granite 3.3 8B Instruct

0 providers
Google

Gemini 2.5 Pro

+10.8%
Avg Score:92.0%
Providers:1
IBM

Granite 3.3 8B Instruct

Avg Score:81.2%
Providers:0