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FusionNet 7Bx2 MoE 14B 4.0bpw H6 EXL2 by LoneStriker

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FusionNet 7Bx2 MoE 14B 4.0bpw H6 EXL2 is an open-source language model by LoneStriker. Features: 14b LLM, VRAM: 6.7GB, Context: 32K, License: mit, MoE, Quantized, LLM Explorer Score: 0.11.

  En   Endpoints compatible   Exl2   Mixtral   Moe   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/LoneStriker/FusionNet_7Bx2_MoE_14B-4.0bpw-h6-exl2 

FusionNet 7Bx2 MoE 14B 4.0bpw H6 EXL2 Benchmarks

LLME Score: 0.11066
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
FusionNet 7Bx2 MoE 14B 4.0bpw H6 EXL2 (LoneStriker/FusionNet_7Bx2_MoE_14B-4.0bpw-h6-exl2)
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FusionNet 7Bx2 MoE 14B 4.0bpw H6 EXL2 Parameters and Internals

Additional Notes 
Fine-tuned model increases performance using the MoE method.
Supported Languages 
en (fine-tuned)
Training Details 
Methodology:
MoE method
LLM NameFusionNet 7Bx2 MoE 14B 4.0bpw H6 EXL2
Repository 🤗https://huggingface.co/LoneStriker/FusionNet_7Bx2_MoE_14B-4.0bpw-h6-exl2 
Model Size14b
Required VRAM6.7 GB
Updated2026-05-19
MaintainerLoneStriker
Model Typemixtral
Model Files  6.7 GB
Supported Languagesen
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/FusionNet_7Bx2_MoE_14B-4.0bpw-h6-exl2.

Rank the FusionNet 7Bx2 MoE 14B 4.0bpw H6 EXL2 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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