Model Comparison

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

Google

Gemini 1.5 Pro

Google

Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M 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 2024, it represents Google's latest advancement in AI technology.

Google

MedGemma 4B IT

Google

MedGemma 4B IT is a multimodal language model developed by Google. The model shows competitive results across 7 benchmarks. It excels particularly in MIMIC CXR (88.9%), DermMCQA (71.8%), PathMCQA (69.8%). 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.

Google

Gemini 1.5 Pro

Google

2024-05-01

Google

MedGemma 4B IT

Google

2025-05-20

1 year newer

Performance Metrics

Context window and performance specifications

Google

Gemini 1.5 Pro

Larger context
Max Context:2.1M
Google

MedGemma 4B IT

Max Context:-
Parameters:4.3B

Performance comparison across key benchmark categories

Google

Gemini 1.5 Pro

vision
+16.2%
72.3%
general
+9.5%
68.9%
Google

MedGemma 4B IT

vision
56.1%
general
59.5%
Knowledge Cutoff
Training data recency comparison

Gemini 1.5 Pro

2023-11-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 1.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Google

MedGemma 4B IT

0 providers
Google

Gemini 1.5 Pro

Avg Score:0.0%
Providers:1
Google

MedGemma 4B IT

Avg Score:0.0%
Providers:0