Llama 3.3 70B
Parameters
70B
Context Length
130K
Modality
Text
Architecture
Dense
License
Llama 3.3 Community License
Release Date
7 Dec 2024
Knowledge Cutoff
Dec 2023
API Pricing (per 1M)
Input: $0.66 · Output: $0.72
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
7x RTX 4090
24GB VRAM
Datacenter
2x NVIDIA A100
80GB VRAM
Apple Silicon
2x Apple M3 Max
128GB VRAM
130,000 tokens
Consumer
10x RTX 4090
24GB VRAM
Datacenter
3x NVIDIA A100
80GB VRAM
Apple Silicon
2x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#132
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.689 | 36 |
Graduate-Level QA | 0.505 | 88 |
General Text | 1317 | 118 |
Coding Index | 0.12 | 128 |
Intelligence Index | 0.08 | 212 |
General Knowledge Reference | 0.86 | 9 |
StackEval Archived | 0.848 | 12 |
QA Assistant Archived | 0.895 | 15 |
Summarization Archived | 0.681 | 22 |
Rankings
Overall Rank
#132
Coding Rank
#121
About Llama 3.3 70B
Llama 3.3 70B is Meta's cost-efficient dense transformer model delivering 405B-class conversational and coding performance in a 70B footprint. It supports multilingual chat across 8 languages and tool integration over a 130K context window.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
64
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
ROPE
RoPE Theta
500,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
8,192
Number of Layers
80
FFN Intermediate Size (Dense)
28,672
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
128,256
About Llama 3.3
Meta's Llama 3.3 is a 70 billion parameter, multilingual large language model. It utilizes an optimized transformer architecture, incorporating Grouped-Query Attention for enhanced inference efficiency. The model features an extended 128k token context window and is designed to support quantization, facilitating deployment on varied hardware configurations.
Other Llama 3.3 Models
- No related models available