Model Comparison

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

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.

Meta

Llama 3.2 11B Instruct

Meta

Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Meta's latest advancement in AI technology.

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

Google

Gemma 3 12B

Google

2025-03-12

5 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemma 3 12B

Input:$0.05
Output:$0.10
Meta

Llama 3.2 11B Instruct

$0.05 cheaper
Input:$0.05
Output:$0.05

Performance Metrics

Context window and performance specifications

Google

Gemma 3 12B

Larger context
Max Context:262.1K
Parameters:12.0B
Meta

Llama 3.2 11B Instruct

Max Context:256.0K
Parameters:10.6B

Average performance across 5 common benchmarks

Google

Gemma 3 12B

+4.8%
Average Score:74.3%
Meta

Llama 3.2 11B Instruct

Average Score:69.5%

Performance comparison across key benchmark categories

Google

Gemma 3 12B

math
+16.5%
73.9%
vision
+8.4%
70.2%
general
53.2%
Meta

Llama 3.2 11B Instruct

math
57.4%
vision
61.8%
general
+16.9%
70.1%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.2 11B Instruct

2023-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 3 12B

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
Meta

Llama 3.2 11B Instruct

6 providers

Sambanova

Throughput: 100 tok/s
Latency: 0.5ms

Together

Throughput: 168 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 108 tok/s
Latency: 0.5ms

Fireworks

Throughput: 125 tok/s
Latency: 0.2ms

Groq

Throughput: 100 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Google

Gemma 3 12B

+4.8%
Avg Score:74.3%
Providers:1
Meta

Llama 3.2 11B Instruct

Avg Score:69.5%
Providers:6