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Mixtral 8x22B Instruct V0.1 GPTQ 4bit by jarrelscy

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Mixtral 8x22B Instruct V0.1 GPTQ 4bit is an open-source language model by jarrelscy. Features: 140.6b LLM, VRAM: 74.1GB, Context: 64K, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

  4-bit   4bit   Conversational   Endpoints compatible   Gptq   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/jarrelscy/Mixtral-8x22B-Instruct-v0.1-GPTQ-4bit 

Mixtral 8x22B Instruct V0.1 GPTQ 4bit Benchmarks

LLME Score: 0.12257
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x22B Instruct V0.1 GPTQ 4bit (jarrelscy/Mixtral-8x22B-Instruct-v0.1-GPTQ-4bit)
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Mixtral 8x22B Instruct V0.1 GPTQ 4bit Parameters and Internals

Model Type 
text generation
Additional Notes 
Quantized to 8-bit using GPTQ technique.
LLM NameMixtral 8x22B Instruct V0.1 GPTQ 4bit
Repository 🤗https://huggingface.co/jarrelscy/Mixtral-8x22B-Instruct-v0.1-GPTQ-4bit 
Model Size140.6b
Required VRAM74.1 GB
Updated2026-06-09
Maintainerjarrelscy
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-15   5.0 GB: 2-of-15   5.0 GB: 3-of-15   5.0 GB: 4-of-15   5.0 GB: 5-of-15   5.0 GB: 6-of-15   5.0 GB: 7-of-15   5.0 GB: 8-of-15   5.0 GB: 9-of-15   5.0 GB: 10-of-15   5.0 GB: 11-of-15   5.0 GB: 12-of-15   5.0 GB: 13-of-15   5.0 GB: 14-of-15   4.1 GB: 15-of-15
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureMixtralForCausalLM
Context Length65536
Model Max Length65536
Transformers Version4.39.3
Tokenizer ClassLlamaTokenizer
Vocabulary Size32768
Torch Data Typefloat16

Best Alternatives to Mixtral 8x22B Instruct V0.1 GPTQ 4bit

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Context / RAM
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... 8x22B Instruct V0.1 GPTQ 8bit64K / 143.8 GB50
Mixtral 8x22B Instruct V0.164K / 221.4 GB65372753
...ixtral 8x22B Instruct V0.1 FP864K / 140.9 GB8510
...ixtral 8x22B Instruct V0.1 AWQ64K / 73.7 GB668913
WizardLM 2 8x22B Beige64K / 221.4 GB794
...igHuggyD Grey WizardLM 2 8x22B64K / 216.6 GB84
...x22B Instruct V0.1 FP8 Dynamic64K / 140.9 GB220
...ral 8x22B Instruct V0.1 FP8 V264K / 140.9 GB50
...ral 8x22B Instruct V0.1 FP8 V164K / 140.9 GB60
Mixtral 8x22B GO Instruct V164K / 280.8 GB172
Note: green Score (e.g. "73.2") means that the model is better than jarrelscy/Mixtral-8x22B-Instruct-v0.1-GPTQ-4bit.

Rank the Mixtral 8x22B Instruct V0.1 GPTQ 4bit 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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