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Llava 1.6 Gptq 8bit by panoyo9829

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Llava 1.6 Gptq 8bit is an open-source language model by panoyo9829. Features: 7b LLM, VRAM: 9.6GB, Context: 32K, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

  8-bit   8bit   Conversational   Endpoints compatible   Gptq   Instruct   Llava   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/panoyo9829/llava-1.6-gptq-8bit 

Llava 1.6 Gptq 8bit Benchmarks

LLME Score: 0.11732
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llava 1.6 Gptq 8bit (panoyo9829/llava-1.6-gptq-8bit)
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Llava 1.6 Gptq 8bit Parameters and Internals

LLM NameLlava 1.6 Gptq 8bit
Repository 🤗https://huggingface.co/panoyo9829/llava-1.6-gptq-8bit 
Model Size7b
Required VRAM9.6 GB
Updated2026-05-14
Maintainerpanoyo9829
Model Typellava
Instruction-BasedYes
Model Files  9.6 GB   0.0 GB
GPTQ QuantizationYes
Quantization Typegptq|8bit
Model ArchitectureLlavaLlamaForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

Best Alternatives to Llava 1.6 Gptq 8bit

Best Alternatives
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Llava V1.6 Mistral 7B PATCHED32K / 15.1 GB178
Quilt Llava V1.5 7B4K / 14.2 GB386429
Table Llava V1.5 7B4K / 14.2 GB2713
Co Instruct Llava V1.5 7B4K / 14.1 GB101
...V1.5 7b Qinstruct Preview V0.14K / 14.2 GB11105
...ct4V LLaVA Instruct Mix880k 7B4K / 14.2 GB83
Chinese LLaVA Baichuan2K / 28 GB319
KoLLaVA KoVicuna 7B2K / 27 GB2613
Note: green Score (e.g. "73.2") means that the model is better than panoyo9829/llava-1.6-gptq-8bit.

Rank the Llava 1.6 Gptq 8bit 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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