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Gradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed by PrunaAI

 »  All LLMs  »  PrunaAI  »  Gradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed   URL Share it on

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Gradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed is an open-source language model by PrunaAI. Features: 8b LLM, VRAM: 5.8GB, Context: 1024K, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

  4-bit   4bit   Awq Base model:gradientai/llama-3-... Base model:quantized:gradienta...   Instruct   Llama   Pruna-ai   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/PrunaAI/gradientai-Llama-3-8B-Instruct-Gradient-1048k-AWQ-4bit-smashed 

Gradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed Benchmarks

LLME Score: 0.13102
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed (PrunaAI/gradientai-Llama-3-8B-Instruct-Gradient-1048k-AWQ-4bit-smashed)
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Gradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed Parameters and Internals

Model Type 
language model, compressed model
Additional Notes 
The smashed model has a measured inference speed, memory, or energy consumption which is less than 90% of the original base model. Results mentioning "first" are obtained after the first run of the model. "Sync" and "Async" metrics could be relevant depending on the use-case.
Training Details 
Data Sources:
WikiText
Methodology:
compressed with AWQ
Hardware Used:
NVIDIA A100-PCIE-40GB
Input Output 
Performance Tips:
Check efficiency gains directly in your use-cases. The first run might take more memory or be slower than subsequent runs due to CUDA overheads.
LLM NameGradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed
Repository 🤗https://huggingface.co/PrunaAI/gradientai-Llama-3-8B-Instruct-Gradient-1048k-AWQ-4bit-smashed 
Base Model(s)  ...a 3 8B Instruct Gradient 1048K   gradientai/Llama-3-8B-Instruct-Gradient-1048k
Model Size8b
Required VRAM5.8 GB
Updated2025-09-23
MaintainerPrunaAI
Model Typellama
Instruction-BasedYes
Model Files  4.7 GB: 1-of-2   1.1 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq|4bit
Model ArchitectureLlamaForCausalLM
Context Length1048576
Model Max Length1048576
Transformers Version4.40.0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than PrunaAI/gradientai-Llama-3-8B-Instruct-Gradient-1048k-AWQ-4bit-smashed.

Rank the Gradientai Llama 3 8B Instruct Gradient 1048K AWQ 4bit Smashed 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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