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Meta Llama 3 8B Instruct W4 Group128 A16 Test by nm-testing

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Meta Llama 3 8B Instruct W4 Group128 A16 Test is an open-source language model by nm-testing. Features: 8b LLM, VRAM: 5.8GB, Context: 8K, Instruction-Based, LLM Explorer Score: 0.14.

  Compressed-tensors   Conversational   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/nm-testing/Meta-Llama-3-8B-Instruct-W4-Group128-A16-Test 

Meta Llama 3 8B Instruct W4 Group128 A16 Test Benchmarks

LLME Score: 0.13703
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 8B Instruct W4 Group128 A16 Test (nm-testing/Meta-Llama-3-8B-Instruct-W4-Group128-A16-Test)
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Meta Llama 3 8B Instruct W4 Group128 A16 Test Parameters and Internals

LLM NameMeta Llama 3 8B Instruct W4 Group128 A16 Test
Repository 🤗https://huggingface.co/nm-testing/Meta-Llama-3-8B-Instruct-W4-Group128-A16-Test 
Model Size8b
Required VRAM5.8 GB
Updated2026-05-19
Maintainernm-testing
Model Typellama
Instruction-BasedYes
Model Files  4.7 GB: 1-of-2   1.1 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.40.2
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

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Cthulhu 8B V1.41048K / 16.1 GB129
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Zero Llama 3.1 8B Beta61048K / 16.1 GB41
Note: green Score (e.g. "73.2") means that the model is better than nm-testing/Meta-Llama-3-8B-Instruct-W4-Group128-A16-Test.

Rank the Meta Llama 3 8B Instruct W4 Group128 A16 Test Capabilities

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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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