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BeyondInfinity V2 4x7B AWQ by solidrust

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BeyondInfinity V2 4x7B AWQ is an open-source language model by solidrust. Features: 24.2b LLM, VRAM: 13GB, Context: 32K, MoE, Quantized, LLM Explorer Score: 0.13.

  4-bit   Autotrain compatible   Awq Base model:quantized:r136a1/be... Base model:r136a1/beyondinfini...   Endpoints compatible   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/solidrust/BeyondInfinity-v2-4x7B-AWQ 

BeyondInfinity V2 4x7B AWQ Benchmarks

LLME Score: 0.13194
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BeyondInfinity V2 4x7B AWQ (solidrust/BeyondInfinity-v2-4x7B-AWQ)
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BeyondInfinity V2 4x7B AWQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
AWQ supports faster Transformers-based inference with equivalent or better quality compared to GPTQ, using 4-bit quantization.
Input Output 
Input Format:
tokens
Accepted Modalities:
text
Output Format:
text
LLM NameBeyondInfinity V2 4x7B AWQ
Repository 🤗https://huggingface.co/solidrust/BeyondInfinity-v2-4x7B-AWQ 
Base Model(s)  BeyondInfinity V2 4x7B   R136a1/BeyondInfinity-v2-4x7B
Model Size24.2b
Required VRAM13 GB
Updated2026-05-14
Maintainersolidrust
Model Typemixtral
Model Files  5.0 GB: 1-of-3   5.0 GB: 2-of-3   3.0 GB: 3-of-3
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.41.0
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 solidrust/BeyondInfinity-v2-4x7B-AWQ.

Rank the BeyondInfinity V2 4x7B 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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