Noromaid V0.1 Mixtral 8x7b Instruct V3 AWQ by TheBloke

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Noromaid V0.1 Mixtral 8x7b Instruct V3 AWQ is an open-source language model by TheBloke. Features: 46.7b LLM, VRAM: 24.7GB, Context: 32K, License: cc-by-nc-4.0, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.11.

  4-bit   Awq Base model:neversleep/noromaid... Base model:quantized:neverslee...   Conversational   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Noromaid V0.1 Mixtral 8x7b Instruct V3 AWQ Benchmarks

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

Noromaid V0.1 Mixtral 8x7b Instruct V3 AWQ Parameters and Internals

Model Type 
mixtral
Additional Notes 
This is an experimental model; don't expect everything to work perfectly.
Training Details 
Data Sources:
Aesir 1 and 2, LimaRP-20231109, ToxicDPO-NoWarning, No-robots-ShareGPT
Methodology:
Modified version of the Alpaca prompting format
Training Time:
28 hours total (v1: 8h, v2: 8h, v3: 12h)
Input Output 
Input Format:
Instruction: {system_message} ### Input: {prompt} ### Response:
LLM NameNoromaid V0.1 Mixtral 8x7b Instruct V3 AWQ
Repository 🤗https://huggingface.co/TheBloke/Noromaid-v0.1-mixtral-8x7b-Instruct-v3-AWQ 
Model NameNoromaid V0.1 Mixtral 8X7B Instruct v3
Model CreatorIkariDev and Undi
Base Model(s)  NeverSleep/Noromaid-v0.1-mixtral-8x7b-Instruct-v3   NeverSleep/Noromaid-v0.1-mixtral-8x7b-Instruct-v3
Model Size46.7b
Required VRAM24.7 GB
Updated2026-04-16
MaintainerTheBloke
Model Typemixtral
Instruction-BasedYes
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Noromaid-v0.1-mixtral-8x7b-Instruct-v3-AWQ.

Rank the Noromaid V0.1 Mixtral 8x7b Instruct V3 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