FrogNano 4B
Parameters
4B
Context Length
262K
Modality
Text
Architecture
Dense
License
MIT License
Release Date
17 Sept 2026
Knowledge Cutoff
-
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
262,144 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
No evaluation benchmarks for FrogNano 4B available.
Rankings
Overall Rank
-
Coding Rank
-
About FrogNano 4B
FrogNano 4B is a compact multimodal language model developed by Microsoft for efficient edge computing and visual reasoning. It adapts dense transformer blocks to deliver strong multimodal performance under strict parameter budgets.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
16
Key-Value Heads
4
Attention Head Dimension
256
Position Embedding
ROPE
RoPE Theta
10,000,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
Yes
Linear Attention Ratio
75.0%
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Auxiliary Parameters
-
Hidden Dimension Size
2,560
Number of Layers
32
FFN Intermediate Size (Dense)
9,216
Multi-Token Prediction Heads
1
Tokenizer
Vocabulary Size
248,320
Resources
About FrogNano
The FrogNano model family developed by Microsoft.
Other FrogNano Models
- No related models available