Gemma 2 2B
Parameters
2B
Context Length
8K
Modality
Text
Architecture
Dense
KV Cache Rate
52 KB/tok
License
Gemma License
Release Date
27 Jun 2024
Knowledge Cutoff
Jun 2024
API Pricing (per 1M)
Self-hosted only
Hardware Sizing
Precision
Context
Workload Memory: 3.84 GB
INT4 · 8K context
Base Weights: 0.93 GB
KV Cache: 0.41 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
1x NVIDIA L4 24GB
3.8 / 21.6 GB usable
1x RTX 3060 12GB
3.8 / 10.8 GB usable
Apple M4 24GB
3.8 / 18.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Architecture Diagram
Evaluation Benchmarks
Rank
#230
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1200 | 183 |
Rankings
Overall Rank
#230
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
Position Embedding
ROPE
Normalization
RMS Normalization
Activation Function
GELU
Dimensions
Hidden Dimension Size
2,048
Number of Layers
26
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.