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.

Meta

Llama 3.2 90B Instruct

Meta

Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. 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 2024, it represents Meta's latest advancement in AI technology.

Meta

Llama 3.2 90B Instruct

Meta

2024-09-25

Google

Gemma 3n E4B Instructed

Google

2025-06-26

9 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemma 3n E4B Instructed

Input:$20.00
Output:$40.00
Meta

Llama 3.2 90B Instruct

$59.25 cheaper
Input:$0.35
Output:$0.40

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E4B Instructed

Max Context:64.0K
Parameters:8.0B
Meta

Llama 3.2 90B Instruct

Larger context
Max Context:256.0K
Parameters:90.0B

Average performance across 3 common benchmarks

Google

Gemma 3n E4B Instructed

Average Score:51.9%
Meta

Llama 3.2 90B Instruct

+21.3%
Average Score:73.2%

Performance comparison across key benchmark categories

Google

Gemma 3n E4B Instructed

general
41.6%
math
52.4%
Meta

Llama 3.2 90B Instruct

general
+31.9%
73.5%
math
+18.4%
70.7%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
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
Meta

Llama 3.2 90B Instruct

5 providers

Together

Throughput: 57 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 42 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 24 tok/s
Latency: 0.5ms

Fireworks

Throughput: 50 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Google

Gemma 3n E4B Instructed

Avg Score:51.9%
Providers:1
Meta

Llama 3.2 90B Instruct

+21.3%
Avg Score:73.2%
Providers:5