Agnes 3.0 Flash
Parameters
33B
Context Length
262K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
11 Sept 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
4x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
262,144 tokens
Consumer
8x RTX 4090
24GB VRAM
Datacenter
2x NVIDIA A100
80GB VRAM
Apple Silicon
2x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for Agnes 3.0 Flash available.
Rankings
Overall Rank
-
Coding Rank
-
About Agnes 3.0 Flash
Agnes 3.0 Flash is a lightweight conditional generation model designed for fast multimodal and conversational tasks. It offers optimized throughput for latency-critical deployment environments.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
24
Key-Value Heads
4
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
Hidden Dimension Size
5,120
Number of Layers
72
FFN Intermediate Size (Dense)
17,408
Multi-Token Prediction Heads
1
Tokenizer
Vocabulary Size
248,320
Resources
About Agnes 3.0
The Agnes 3.0 model family developed by Agnes AI.
Other Agnes 3.0 Models
- No related models available