Nethena 20B Glued AWQ by TheBloke

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Nethena 20B Glued AWQ is an open-source language model by TheBloke. Features: 20b LLM, VRAM: 10.9GB, Context: 4K, License: cc-by-nc-4.0, Quantized, LLM Explorer Score: 0.11.

  4-bit   Awq Base model:athirdpath/nethena-... Base model:quantized:athirdpat...   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Nethena 20B Glued AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Nethena 20B Glued AWQ Parameters and Internals

Model Type 
llama
Additional Notes 
The model was quantized using AWQ for efficient, low-bit weight quantization, suitable for NVidia GPUs, supporting faster inference.
Training Details 
Data Volume:
~500k tokens
Methodology:
Alpaca-style prompts
Context Length:
2048
LLM NameNethena 20B Glued AWQ
Repository 🤗https://huggingface.co/TheBloke/Nethena-20B-Glued-AWQ 
Model NameNethena 20B Glued
Model CreatorRaven
Base Model(s)  Nethena 20B Glued   athirdpath/Nethena-20b-Glued
Model Size20b
Required VRAM10.9 GB
Updated2026-05-11
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   0.9 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length4096
Model Max Length4096
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token[PAD]
Vocabulary Size32001
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Nethena-20B-Glued-AWQ.

Rank the Nethena 20B Glued 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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Release v20260328a