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Meta Llama 3 70B Instruct by meta-llama

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Model Card on HF 🤗: https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct 

Meta Llama 3 70B Instruct Benchmarks

MMLU Pro: 46.74
GPQA: 4.92
MUSR: 10.92
BBH: 50.19
IFEval: 80.99 vs 88 (so35)-8%
ARC: 71.42 vs 96.7 (so35)-26.1%
HellaSwag: 85.69 vs 95.3 (gpt4)-10.1%
MMLU: 80.06 vs 88.3 (so35)-9.3%
TruthfulQA: 61.81 vs 59 (gpt4)4.8%
WinoGrande: 82.87 vs 87.5 (gpt4)-5.3%
GSM8K: 85.44 vs 96.4 (so35)-11.4%
MATH Lvl 5: 24.47
LLME Score: 0.43874
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3 70B Instruct (meta-llama/Meta-Llama-3-70B-Instruct)
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Meta Llama 3 70B Instruct Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
commercial, research
Applications:
chatbot, NLP tasks
Primary Use Cases:
Instruction tuned models for assistant-like chat
Limitations:
English only, compliance with policies required
Supported Languages 
en (optimised)
Training Details 
Data Sources:
publicly available online data, instruction datasets, 10M human-annotated examples
Data Volume:
15T+ tokens
Methodology:
Pretraining, fine-tuning, reinforcement learning with human feedback
Context Length:
8000
Hardware Used:
H100-80GB GPUs
Model Architecture:
Optimized transformer architecture, auto-regressive
Safety Evaluation 
Methodologies:
Red teaming, Adversarial evaluations, Safety mitigations
Findings:
Llama 3 has enhanced measures to reduce residual risks
Risk Categories:
Cybersecurity, Child Safety, General misuse
Responsible Ai Considerations 
Mitigation Strategies:
Implement safety tools, community feedback
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text, code
Release Notes 
Version:
3.1
Notes:
Release of instruction tuned models optimized for dialogue use cases
LLM NameMeta Llama 3 70B Instruct
Repository 🤗https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct 
Base Model(s)  Meta Llama 3 70B   meta-llama/Meta-Llama-3-70B
Model Size70b
Required VRAM141.9 GB
Updated2025-09-23
Maintainermeta-llama
Model Typellama
Instruction-BasedYes
Model Files  4.6 GB: 1-of-30   4.7 GB: 2-of-30   5.0 GB: 3-of-30   5.0 GB: 4-of-30   4.7 GB: 5-of-30   4.7 GB: 6-of-30   4.7 GB: 7-of-30   5.0 GB: 8-of-30   5.0 GB: 9-of-30   4.7 GB: 10-of-30   4.7 GB: 11-of-30   4.7 GB: 12-of-30   5.0 GB: 13-of-30   5.0 GB: 14-of-30   4.7 GB: 15-of-30   4.7 GB: 16-of-30   4.7 GB: 17-of-30   5.0 GB: 18-of-30   5.0 GB: 19-of-30   4.7 GB: 20-of-30   4.7 GB: 21-of-30   4.7 GB: 22-of-30   5.0 GB: 23-of-30   5.0 GB: 24-of-30   4.7 GB: 25-of-30   4.7 GB: 26-of-30   4.7 GB: 27-of-30   5.0 GB: 28-of-30   5.0 GB: 29-of-30   2.1 GB: 30-of-30
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensellama3
Context Length8192
Model Max Length8192
Transformers Version4.40.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

Quantized Models of the Meta Llama 3 70B Instruct

Model
Likes
Downloads
VRAM
Meta Llama 3 70B Instruct GPTQ19176339 GB
...ma3 70B Chinese Chat GGUF 4bit1854540 GB
Meta Llama 3 70B Instruct GGUF413326 GB
...oLLM Llama3 70B 6.0bpw H6 EXL20854 GB
...LLM Llama3 70B 4.65bpw H6 EXL20842 GB
...oLLM Llama3 70B 4.0bpw H6 EXL20837 GB
...oLLM Llama3 70B 2.4bpw H6 EXL20823 GB
Llama3 70B Instruct 4bit11339 GB

Best Alternatives to Meta Llama 3 70B Instruct

Best Alternatives
Context / RAM
Downloads
Likes
... Chat 1048K Chinese Llama3 70B1024K / 141.9 GB98265
... Chat 1048K Chinese Llama3 70B1024K / 141.9 GB90695
... 3 70B Instruct Gradient 1048K1024K / 141.9 GB13122
Llama3 Function Calling 1048K1024K / 141.9 GB61
...a 3 70B Instruct Gradient 524K512K / 141.9 GB1023
...a 3 70B Instruct Gradient 262K256K / 141.9 GB11456
...ama 3 70B Arimas Story RP V2.0256K / 141.1 GB263
...ama 3 70B Arimas Story RP V1.6256K / 141.2 GB130
...ama 3 70B Arimas Story RP V1.5256K / 141.2 GB463
Llama 3.1 70B Instruct128K / 141.9 GB888766849
Note: green Score (e.g. "73.2") means that the model is better than meta-llama/Meta-Llama-3-70B-Instruct.

Rank the Meta Llama 3 70B Instruct Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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