Model Comparison

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

Google

Gemini 2.0 Flash

Google

Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). 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 2024, it represents Google's latest advancement in AI technology.

Google

Gemma 3 4B

Google

Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. 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.

Google

Gemini 2.0 Flash

Google

2024-12-01

Google

Gemma 3 4B

Google

2025-03-12

3 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.0 Flash

Input:$0.10
Output:$0.40
Google

Gemma 3 4B

$0.44 cheaper
Input:$0.02
Output:$0.04

Performance Metrics

Context window and performance specifications

Google

Gemini 2.0 Flash

Larger context
Max Context:1.1M
Google

Gemma 3 4B

Max Context:262.1K
Parameters:4.0B

Average performance across 8 common benchmarks

Google

Gemini 2.0 Flash

+22.2%
Average Score:70.0%
Google

Gemma 3 4B

Average Score:47.8%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash

factuality
+13.5%
83.6%
math
+11.9%
76.4%
vision
+11.7%
70.7%
general
+21.9%
62.6%
code
61.4%
Google

Gemma 3 4B

factuality
70.1%
math
64.5%
vision
59.0%
general
40.7%
code
+0.1%
61.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.0 Flash

2024-08-01

Gemma 3 4B

2024-08-01

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

1 providers

Google

Throughput: 183 tok/s
Latency: 0.4ms
Google

Gemma 3 4B

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
Google

Gemini 2.0 Flash

+22.2%
Avg Score:70.0%
Providers:1
Google

Gemma 3 4B

Avg Score:47.8%
Providers:1