Ling 3.0 Flash VL
Active Parameters
124B
Context Length
131K
Modality
Text
Architecture
Mixture of Experts
KV Cache Rate
47 KB/tok
License
MIT License
Release Date
4 Sept 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.07 · Output: $0.22
Hardware Sizing
Precision
Context
Workload Memory: 248.96 GB
FP16 · 8K context
Base Weights: 241.21 GB
KV Cache: 5.25 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
8x NVIDIA H100 80GB
249.0 / 576.0 GB usable · TP 8
Determine requirements for your specific workload:
Open in VRAM Calculator
Architecture Diagram
Evaluation Benchmarks
Rank
#83
| Benchmark | Score | Rank |
|---|---|---|
Agentic Index | 0.29 | 64 |
Coding Index | 0.57 | 72 |
Intelligence Index | 0.25 | 113 |
Rankings
Overall Rank
#83
Coding Rank
#60
About Ling 3.0 Flash VL
Ling 3.0 Flash VL is a vision-language multimodal foundation model built on a Mixture-of-Experts architecture. It is optimized for efficient high-speed visual reasoning and document understanding.
Technical Specifications
Attention
Attention Structure
Multi-Layer Attention
Attention Heads
32
Key-Value Heads
32
Attention Head Dimension
128
Position Embedding
ROPE
RoPE Theta
6,000,000
Linear Attention
Yes
Linear Attention Ratio
83.3%
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
2,560
Number of Layers
42
FFN Intermediate Size (Dense)
6,144
Tokenizer
Vocabulary Size
157,184
Mixture of Experts
Total Expert Parameters
5.5B
Number of Experts
512
Active Experts
8
FFN Intermediate Size (per Expert)
768
Dense Layers Before MoE
2
Resources
About Ling
The Ling model family developed by InclusionAI.