Model Comparison

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

Google

Gemma 3n E4B Instructed LiteRT Preview

Google

Gemma 3n E4B Instructed LiteRT Preview is a multimodal language model developed by Google. The model shows competitive results across 28 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). 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 Google's latest advancement in AI technology.

Alibaba

Qwen2.5 72B Instruct

Alibaba

Qwen2.5 72B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 77.4% across 14 benchmarks. It excels particularly in GSM8k (95.8%), MT-Bench (93.5%), MBPP (88.2%). The model shows particular specialization in math tasks with an average performance of 89.5%. It supports a 139K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5 72B Instruct

Alibaba

2024-09-19

Google

Gemma 3n E4B Instructed LiteRT Preview

Google

2025-05-20

8 months newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E4B Instructed LiteRT Preview

Max Context:-
Parameters:1.9B
Alibaba

Qwen2.5 72B Instruct

Larger context
Max Context:139.3K
Parameters:72.7B

Average performance across 5 common benchmarks

Google

Gemma 3n E4B Instructed LiteRT Preview

Average Score:45.2%
Alibaba

Qwen2.5 72B Instruct

+24.9%
Average Score:70.1%

Performance comparison across key benchmark categories

Google

Gemma 3n E4B Instructed LiteRT Preview

math
49.2%
code
38.9%
general
48.4%
Alibaba

Qwen2.5 72B Instruct

math
+40.3%
89.5%
code
+39.7%
78.6%
general
+25.8%
74.1%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B Instructed LiteRT Preview

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 LiteRT Preview

0 providers
Alibaba

Qwen2.5 72B Instruct

4 providers

Together

Throughput: 47 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 10 tok/s
Latency: 0.5ms

Fireworks

Throughput: 59 tok/s
Latency: 0.37ms
Google

Gemma 3n E4B Instructed LiteRT Preview

Avg Score:45.2%
Providers:0
Alibaba

Qwen2.5 72B Instruct

+24.9%
Avg Score:70.1%
Providers:4