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Mixtralnt 4x7b Test AWQ by TheBloke

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Mixtralnt 4x7b Test AWQ is an open-source language model by TheBloke. Features: 24.2b LLM, VRAM: 13GB, Context: 32K, License: cc-by-nc-4.0, MoE, Quantized, LLM Explorer Score: 0.11.

  4-bit   Awq Base model:chargoddard/mixtral... Base model:quantized:chargodda...   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/mixtralnt-4x7b-test-AWQ 

Mixtralnt 4x7b Test AWQ Benchmarks

LLME Score: 0.10708
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtralnt 4x7b Test AWQ (TheBloke/mixtralnt-4x7b-test-AWQ)
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Mixtralnt 4x7b Test AWQ Parameters and Internals

Model Type 
mixtral
Additional Notes 
TheBloke's LLM work is supported by a grant from Andreessen Horowitz (a16z).
Input Output 
Input Format:
{prompt}
LLM NameMixtralnt 4x7b Test AWQ
Repository 🤗https://huggingface.co/TheBloke/mixtralnt-4x7b-test-AWQ 
Model NameMixtralnt 4X7B Test
Model CreatorCharles Goddard
Base Model(s)  Mixtralnt 4x7b Test   chargoddard/mixtralnt-4x7b-test
Model Size24.2b
Required VRAM13 GB
Updated2026-05-11
MaintainerTheBloke
Model Typemixtral
Model Files  10.0 GB: 1-of-2   3.0 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/mixtralnt-4x7b-test-AWQ.

Rank the Mixtralnt 4x7b Test AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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