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ai/llama3.1

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By Docker

•Updated over 1 year ago

Meta’s LLama 3.1: Chat-focused, benchmark-strong, multilingual-ready.

Model
6

50K+

ai/llama3.1 repository overview

⁠Llama 3.1

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​Meta Llama 3.1 is a collection of multilingual large language models (LLMs) available in 8B, 70B and 405B parameter sizes. These models are designed for text-based tasks, including chat and content generation. The instruction-tuned versions available here are optimized for multilingual dialogue use cases and have demonstrated superior performance compared to many open-source and commercial chat models on common industry benchmarks.

⁠Intended uses

  • Assistant-like chat: Instruction-tuned text-only models are optimized for multilingual dialogue, making them ideal for developing conversational AI assistants. ​

  • Natural language generation tasks: Pretrained models can be adapted for various text-based applications, such as content creation, summarization, and translation. ​

  • Synthetic data generation: Utilize the outputs of Llama 3.1 to create synthetic datasets, which can aid in training and improving other models. ​

  • Model distillation: Leverage Llama 3.1 to enhance smaller models by transferring knowledge, resulting in more efficient and specialized AI systems, or by using it as a base model to fine-tune based on the knowledge of other bigger models (see deepseek-r1-distill-llama as an example) ​

  • Research purposes: Employ Llama 3.1 in academic and scientific research to explore advancements in natural language processing and artificial intelligence.

⁠Characteristics

AttributeDetails
ProviderMeta
Architecturellama
Cutoff dateDecember 2023
LanguagesEnglish, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
Tool calling✅
Input modalitiesText
Output modalitiesText and Code
LicenseLlama 3.1 Community license⁠

⁠Available model variants

Model variantParametersQuantizationContext windowVRAM¹Size
ai/llama3.1:latest

ai/llama3.1:8B-Q4_K_M
8BIQ2_XXS/Q4_K_M131K tokens5.33 GiB4.58 GB
ai/llama3.1:8B-Q4_K_M8BIQ2_XXS/Q4_K_M131K tokens5.33 GiB4.58 GB
ai/llama3.1:8B-F168BF16131K tokens15.01 GiB14.96 GB

¹: VRAM estimated based on model characteristics.

latest → 8B-Q4_K_M

⁠Use this AI model with Docker Model Runner

First, pull the model:

docker model pull ai/llama3.1

Then run the model:

docker model run ai/llama3.1

For more information on Docker Model Runner, explore the documentation⁠.

⁠Benchmark performance

CategoryBenchmarkLlama 3.1 8B
GeneralMMLU69.4
MMLU (CoT)73.0
MMLU-Pro (CoT)48.3
IFEval80.4
ReasoningARC-C83.4
GPQA30.4
CodeHumanEval72.6
MBPP ++ base version72.8
Multipl-E HumanEval50.8
Multipl-E MBPP52.4
MathGSM-8K (CoT)84.5
MATH (CoT)51.9
Tool UseAPI-Bank82.6
BFCL76.1
Gorilla Benchmark API Bench8.2
Nexus (0-shot)38.5
MultilingualMultilingual MGSM (CoT)68.9
MMLU (5-shot) - Portuguese62.12
MMLU (5-shot) - Spanish62.45
MMLU (5-shot) - Italian61.63
MMLU (5-shot) - German60.59
MMLU (5-shot) - French62.34
MMLU (5-shot) - Hindi50.88
MMLU (5-shot) - Thai50.32

Tag summary

Content type

Model

Digest

sha256:c2d45031a…

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4.6 GB

Last updated

over 1 year ago

docker model pull ai/llama3.1

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