LFM2-VL 3B
Parameters
3B
Context Length
33K
Modality
Text
Architecture
Dense
License
other
Release Date
5 Oct 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
32,768 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
No evaluation benchmarks for LFM2-VL 3B available.
Rankings
Overall Rank
-
Coding Rank
-
About LFM2-VL 3B
LFM2-VL 3B is a compact multimodal language foundation model developed by Liquid AI based on the Liquid Foundation Model architecture. It is optimized for efficient on-device visual reasoning, document parsing, and edge deployment.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
64
Position Embedding
ROPE
RoPE Theta
1,000,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
Yes
Linear Attention Ratio
73.3%
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Auxiliary Parameters
-
Hidden Dimension Size
2,048
Number of Layers
30
FFN Intermediate Size (Dense)
10,752
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
128,000
Resources
About LFM2
The LFM2 model family developed by Liquid AI.
Other LFM2 Models
- No related models available