Model Comparison

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

Google

Gemini 2.0 Flash-Lite

Google

Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). 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.

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

Gemini 2.0 Flash-Lite

Google

2025-02-05

Google

Gemma 3n E4B Instructed

Google

2025-06-26

4 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.0 Flash-Lite

$59.63 cheaper
Input:$0.07
Output:$0.30
Google

Gemma 3n E4B Instructed

Input:$20.00
Output:$40.00

Performance Metrics

Context window and performance specifications

Google

Gemini 2.0 Flash-Lite

Larger context
Max Context:1.1M
Google

Gemma 3n E4B Instructed

Max Context:64.0K
Parameters:8.0B

Average performance across 5 common benchmarks

Google

Gemini 2.0 Flash-Lite

+16.7%
Average Score:57.1%
Google

Gemma 3n E4B Instructed

Average Score:40.4%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash-Lite

math
+18.7%
71.0%
general
+13.9%
55.5%
code
28.9%
Google

Gemma 3n E4B Instructed

math
52.4%
general
41.6%
code
+10.0%
38.9%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.0 Flash-Lite

2024-06-01

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

Gemini 2.0 Flash-Lite

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Google

Gemma 3n E4B Instructed

1 providers

Together

Throughput: 42.09 tok/s
Latency: 0.43ms
Google

Gemini 2.0 Flash-Lite

+16.7%
Avg Score:57.1%
Providers:1
Google

Gemma 3n E4B Instructed

Avg Score:40.4%
Providers:1