Gemma 3 4B
Parameters
4B
Context Length
131K
Modality
Multimodal
Architecture
Dense
License
Gemma License
Release Date
12 Mar 2025
Knowledge Cutoff
Aug 2024
API Pricing (per 1M)
Input: $0.00 · Output: $0.00
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
131,072 tokens
Consumer
2x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#170
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.436 | 57 |
Graduate-Level QA | 0.308 | 115 |
General Text | 1303 | 140 |
Coding Index | 0.03 | 150 |
Intelligence Index | 1 | 249 |
Rankings
Overall Rank
#170
Coding Rank
#135
About Gemma 3 4B
Gemma 3 4B is a lightweight vision-language model by Google optimized for efficient execution on consumer GPUs, laptops, and edge devices. It supports multimodal inputs, function calling, and over 140 languages across a 128K context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
-
Position Embedding
ROPE
RoPE Theta
-
Sliding Window Attention
-
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
-
Dimensions
Hidden Dimension Size
2,048
Number of Layers
30
FFN Intermediate Size (Dense)
-
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
-
About Gemma 3
Gemma 3 is a family of open, lightweight models from Google. It introduces multimodal image and text processing, supports over 140 languages, and features extended context windows up to 128K tokens. Models are available in multiple parameter sizes for diverse applications.