Falcon3-7B
Parameters
7B
Context Length
32K
Modality
Text
Architecture
Dense
License
TII Falcon-LLM License 2.0
Release Date
17 Dec 2024
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
32,000 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 Falcon3-7B available.
Rankings
Overall Rank
-
Coding Rank
-
About Falcon3-7B
Falcon3-7B is a state-of-the-art instruction-tuned language model from TII optimized for STEM problem-solving, code generation, and research assistance. Pretrained on 14T tokens, it supports multilingual inference across a 32K context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
256
Position Embedding
ROPE
RoPE Theta
1,000,042
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
36
FFN Intermediate Size (Dense)
23,040
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
131,072
About Falcon 3
The TII Falcon 3 model family comprises open-source, decoder-only language models (1B-10B parameters) designed for efficiency. Key innovations include an extended 32K token context window, Grouped-Query Attention (GQA), and specialized versions for scientific and code-oriented applications. Some variants integrate Mamba-based architectures.