Model Comparison

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

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.

IBM

Granite 3.3 8B Instruct

IBM

Granite 3.3 8B Instruct is a multimodal language model developed by IBM. It achieves strong performance with an average score of 69.8% across 14 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). The model shows particular specialization in code tasks with an average performance of 78.3%. 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 IBM's latest advancement in AI technology.

Google

Gemma 3 4B

Google

2025-03-12

IBM

Granite 3.3 8B Instruct

IBM

2025-04-16

1 month newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3 4B

Larger context
Max Context:262.1K
Parameters:4.0B
IBM

Granite 3.3 8B Instruct

Max Context:-
Parameters:8.0B

Average performance across 4 common benchmarks

Google

Gemma 3 4B

+2.1%
Average Score:80.7%
IBM

Granite 3.3 8B Instruct

Average Score:78.6%

Performance comparison across key benchmark categories

Google

Gemma 3 4B

code
61.5%
math
64.5%
factuality
+3.2%
70.1%
general
40.7%
IBM

Granite 3.3 8B Instruct

code
+16.8%
78.3%
math
+10.5%
75.0%
factuality
66.9%
general
+23.3%
63.9%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Granite 3.3 8B Instruct

2024-04-01

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

Gemma 3 4B

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
IBM

Granite 3.3 8B Instruct

0 providers
Google

Gemma 3 4B

+2.1%
Avg Score:80.7%
Providers:1
IBM

Granite 3.3 8B Instruct

Avg Score:78.6%
Providers:0