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Gemma 2 9B Instruct 4Bit GPTQ by Granther

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Gemma 2 9B Instruct 4Bit GPTQ is an open-source language model by Granther. Features: 9b LLM, VRAM: 6.2GB, Context: 8K, License: gemma, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

  4-bit   4bit Base model:google/gemma-2-9b-i... Base model:quantized:google/ge...   Conversational   Gemma2   Gptq   Instruct   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Granther/Gemma-2-9B-Instruct-4Bit-GPTQ 

Gemma 2 9B Instruct 4Bit GPTQ Benchmarks

LLME Score: 0.13834
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gemma 2 9B Instruct 4Bit GPTQ (Granther/Gemma-2-9B-Instruct-4Bit-GPTQ)
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Gemma 2 9B Instruct 4Bit GPTQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model was quantized with the Auto-GPTQ library.
LLM NameGemma 2 9B Instruct 4Bit GPTQ
Repository 🤗https://huggingface.co/Granther/Gemma-2-9B-Instruct-4Bit-GPTQ 
Model NameGemma-2-9B-Instruct-4Bit-GPTQ
Base Model(s)  Gemma 2 9B It   google/gemma-2-9b-it
Model Size9b
Required VRAM6.2 GB
Updated2026-04-22
MaintainerGranther
Model Typegemma2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   1.2 GB: 2-of-2
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.43.0.dev0
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typefloat16

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GaMS 9B Instruct8K / 18.6 GB16332
Note: green Score (e.g. "73.2") means that the model is better than Granther/Gemma-2-9B-Instruct-4Bit-GPTQ.

Rank the Gemma 2 9B Instruct 4Bit GPTQ 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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