Gemma 2 2B
Parameters
2B
Context Length
8K
Modality
Text
Architecture
Dense
License
Gemma License
Release Date
27 Jun 2024
Knowledge Cutoff
Jun 2024
API Pricing (per 1M)
Self-hosted only
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
8,192 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#188
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1200 | 159 |
Rankings
Overall Rank
#188
Coding Rank
-
About Gemma 2 2B
Gemma 2 2B is a compact, open-weights language model developed by Google for resource-constrained edge and mobile deployments. Distilled from larger Gemini architectures, it provides efficient reasoning and text generation with low memory overhead.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
16
Key-Value Heads
4
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
GELU
Dimensions
Hidden Dimension Size
2,048
Number of Layers
26
FFN Intermediate Size (Dense)
-
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
-
About Gemma 2
Gemma 2 is Google's family of open large language models, offering 2B, 9B, and 27B parameter sizes. Built upon the Gemma architecture, it incorporates innovations such as interleaved local and global attention, logit soft-capping for training stability, and Grouped Query Attention for inference efficiency. The smaller models leverage knowledge distillation.