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Llama 3.1 405B

Parameters

405B

Context Length

128K

Modality

Text

Architecture

Dense

KV Cache Rate

504 KB/tok

License

Llama 3.1 Community License Agreement

Release Date

23 Jul 2024

Knowledge Cutoff

Dec 2023

API Pricing (per 1M)

Input: $4.00 · Output: $4.00

Hardware Sizing

Precision

Context

Workload Memory: 760.81 GB

FP16 · 8K context

Base Weights: 754.37 GB

KV Cache: 3.94 GB

Runtime & Graphs: 2.50 GB

Minimum Required Hardware

8x NVIDIA H200 141GB

760.8 / 1015.2 GB usable · TP 8

Determine requirements for datacenter hardware:

Upgrade to Pro

Architecture Diagram

Input TokensToken EmbeddingPosition: RoPEHidden: 16.4k · Context: 128Kx 126 layersRMSNormPre-AttentionGrouped-Query Attention128Q / 8KV headsHead dim: 128+RMSNormPre-FFNFeed-Forward NetworkSwiGLU+Final RMSNormOutput Logits

Evaluation Benchmarks

Rank

#156

BenchmarkScoreRank

Professional Knowledge

MMLU Pro

0.733

40

Graduate-Level QA

GPQA

0.507

102

General Text

Text Arena

1335

142

Intelligence Index

Artificial Analysis

0.07

267

General Knowledge

Reference
MMLU

0.873

8

StackEval

Archived
ProLLM Stack Eval

0.8

14

QA Assistant

Archived
ProLLM QA Assistant

0.884

16

Rankings

Overall Rank

#156

Coding Rank

-

About Llama 3.1 405B

Llama 3.1 405B is Meta's flagship dense open foundation model pretrained on over 15T tokens across 16,000 GPUs. It delivers state-of-the-art steerability, synthetic data generation, and complex multi-step reasoning over a 128K context window.

Technical Specifications

Attention

Attention Structure

Grouped-Query Attention

Attention Heads

128

Key-Value Heads

8

Position Embedding

ROPE

Normalization

RMS Normalization

Activation Function

SwigLU

Dimensions

Hidden Dimension Size

16,384

Number of Layers

126

About Llama 3.1

Llama 3.1 is Meta's advanced large language model family, building upon Llama 3. It features an optimized decoder-only transformer architecture, available in 8B, 70B, and 405B parameter versions. Significant enhancements include an expanded 128K token context window and improved multilingual capabilities across eight languages, refined through data and post-training procedures.


Other Llama 3.1 Models