MiniCPM-V 4.7 1B
Parameters
1B
Context Length
262K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
6 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
262,144 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 MiniCPM-V 4.7 1B available.
Rankings
Overall Rank
-
Coding Rank
-
About MiniCPM-V 4.7 1B
MiniCPM-V 4.7 1B is an ultra-compact multimodal model tailored for edge deployment and on-device vision-language tasks. It delivers competitive optical character recognition and multimodal conversational performance despite its small footprint.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
8
Key-Value Heads
2
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
1,024
Number of Layers
24
FFN Intermediate Size (Dense)
3,584
Multi-Token Prediction Heads
1
Tokenizer
Vocabulary Size
248,094
Resources
About MiniCPM
The MiniCPM model family developed by OpenBMB.