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Llama 3 8B Synthia V3.5 AWQ by solidrust

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Llama 3 8B Synthia V3.5 AWQ is an open-source language model by solidrust. Features: 8b LLM, VRAM: 5.8GB, Context: 8K, Quantized, LLM Explorer Score: 0.15, Arc: 61.5, HellaSwag: 80.9, MMLU: 65, GSM8K: 63.

  4-bit   Autotrain compatible   Awq Base model:migtissera/llama-3-... Base model:quantized:migtisser...   Conversational   Endpoints compatible   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/solidrust/Llama-3-8B-Synthia-v3.5-AWQ 

Llama 3 8B Synthia V3.5 AWQ Benchmarks

ARC: 61.52 vs 96.7 (so35)-36.4%
HellaSwag: 80.94 vs 95.3 (gpt4)-15.1%
MMLU: 65.02 vs 88.3 (so35)-26.4%
GSM8K: 63 vs 96.4 (so35)-34.6%
LLME Score: 0.14504
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 8B Synthia V3.5 AWQ (solidrust/Llama-3-8B-Synthia-v3.5-AWQ)
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Llama 3 8B Synthia V3.5 AWQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
AWQ facilitates low-bit 4-bit quantization, aiming for efficient and faster inference without sacrificing quality.
Input Output 
Input Format:
The expected input format is a sequence of tokens formatted using a specific prompt template.
Accepted Modalities:
text
Output Format:
The generated output is text, similar to many text generation models.
Performance Tips:
For optimized performance, ensure the model is running on NVidia GPUs and the relevant libraries are installed.
LLM NameLlama 3 8B Synthia V3.5 AWQ
Repository 🤗https://huggingface.co/solidrust/Llama-3-8B-Synthia-v3.5-AWQ 
Base Model(s)  migtissera/Llama-3-8B-Synthia-v3.5   migtissera/Llama-3-8B-Synthia-v3.5
Model Size8b
Required VRAM5.8 GB
Updated2026-04-30
Maintainersolidrust
Model Typellama
Model Files  4.7 GB: 1-of-2   1.1 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.41.1
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than solidrust/Llama-3-8B-Synthia-v3.5-AWQ.

Rank the Llama 3 8B Synthia V3.5 AWQ 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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