ERNIE-4.5-VL-424B-A47B-Base
Active Parameters
424B
Context Length
131K
Modality
Multimodal
Auxiliary Parameters
600M
Architecture
Mixture of Experts
KV Cache Rate
216 KB/tok
License
Apache 2.0
Release Date
30 Jun 2025
Knowledge Cutoff
Jun 2025
API Pricing (per 1M)
Self-hosted only
Hardware Sizing
Precision
Context
Workload Memory: 881.49 GB
FP16 · 8K context
Base Weights: 877.31 GB
KV Cache: 1.69 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
8x NVIDIA H200 141GB
881.5 / 1015.2 GB usable · TP 8
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Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for ERNIE-4.5-VL-424B-A47B-Base available.
Rankings
Overall Rank
-
Coding Rank
-
About ERNIE-4.5-VL-424B-A47B-Base
ERNIE-4.5-VL-424B-Base is Baidu's flagship multimodal Mixture-of-Experts base model activating 47B parameters for cross-modal pretraining. Built with modality-isolated routing, it enables scalable vision-language reasoning over a 131K context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
64
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
500,000
Normalization
RMS Normalization
Activation Function
Swish
Dimensions
Auxiliary Parameters
600M
Hidden Dimension Size
4,096
Number of Layers
54
FFN Intermediate Size (Dense)
28,672
Tokenizer
Vocabulary Size
103,424
Mixture of Experts
Total Expert Parameters
47.0B
Number of Experts
128
Active Experts
16
Dense Layers Before MoE
3
About ERNIE 4.5
The Baidu ERNIE 4.5 family consists of ten large-scale multimodal models. They utilize a heterogeneous Mixture-of-Experts (MoE) architecture, which enables parameter sharing across modalities while also employing dedicated parameters for specific modalities, supporting efficient language and multimodal processing.