Model Comparison

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

Google

Gemini 1.5 Pro

Google

Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M 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 12B

Google

Gemma 3 12B is a multimodal language model developed by Google. It achieves strong performance with an average score of 63.8% across 26 benchmarks. It excels particularly in GSM8k (94.4%), IFEval (88.9%), DocVQA (87.1%). 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 1.5 Pro

Google

2024-05-01

Google

Gemma 3 12B

Google

2025-03-12

10 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 1.5 Pro

Input:$2.50
Output:$10.00
Google

Gemma 3 12B

$12.35 cheaper
Input:$0.05
Output:$0.10

Performance Metrics

Context window and performance specifications

Google

Gemini 1.5 Pro

Larger context
Max Context:2.1M
Google

Gemma 3 12B

Max Context:262.1K
Parameters:12.0B

Average performance across 8 common benchmarks

Google

Gemini 1.5 Pro

+4.6%
Average Score:77.9%
Google

Gemma 3 12B

Average Score:73.3%

Performance comparison across key benchmark categories

Google

Gemini 1.5 Pro

math
+1.0%
74.9%
code
+3.9%
74.5%
vision
+2.1%
72.3%
general
+15.7%
68.9%
Google

Gemma 3 12B

math
73.9%
code
70.5%
vision
70.2%
general
53.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 1.5 Pro

2023-11-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 1.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Google

Gemma 3 12B

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
Google

Gemini 1.5 Pro

+4.6%
Avg Score:77.9%
Providers:1
Google

Gemma 3 12B

Avg Score:73.3%
Providers:1