Gemma 3 270M
Parameters
270M
Context Length
32K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
14 Aug 2025
Knowledge Cutoff
Aug 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
32,000 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
#190
| Benchmark | Score | Rank |
|---|---|---|
Intelligence Index | 0.05 | 282 |
Rankings
Overall Rank
#190
Coding Rank
-
About Gemma 3 270M
Gemma 3 270M is Google's ultra-compact open-weights text model engineered for on-device classification, entity extraction, and edge routing. It features a 256K vocabulary supporting 140+ languages across a 32K token context window.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
16
Key-Value Heads
16
Attention Head Dimension
-
Position Embedding
Absolute Position Embedding
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
1,024
Number of Layers
12
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.