Model Comparison

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

Google

Gemma 3n E4B Instructed

Google

Gemma 3n E4B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (75.0%), MGSM (67.0%), MMLU (64.9%). 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.

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

MedGemma 4B IT

Google

2025-05-20

Google

Gemma 3n E4B Instructed

Google

2025-06-26

1 month newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E4B Instructed

Larger context
Max Context:64.0K
Parameters:8.0B
Google

MedGemma 4B IT

Max Context:-
Parameters:4.3B

Performance comparison across key benchmark categories

Google

Gemma 3n E4B Instructed

general
41.6%
Google

MedGemma 4B IT

general
+17.9%
59.5%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B Instructed

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 3n E4B Instructed

1 providers

Together

Throughput: 42.09 tok/s
Latency: 0.43ms
Google

MedGemma 4B IT

0 providers
Google

Gemma 3n E4B Instructed

Avg Score:0.0%
Providers:1
Google

MedGemma 4B IT

Avg Score:0.0%
Providers:0