What are the hardware requirements for FusionNet 34Bx2 MoE GGUF?

FusionNet 34Bx2 MoE GGUF requires approximately 22.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed FusionNet 34Bx2 MoE GGUF and how large is it?

FusionNet 34Bx2 MoE GGUF is developed by TheBloke. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate FusionNet 34Bx2 MoE GGUF?

FusionNet 34Bx2 MoE GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

FusionNet 34Bx2 MoE GGUF by TheBloke — VRAM 22.4GB

Name: FusionNet 34Bx2 MoE GGUF
Author: TheBloke

FusionNet 34Bx2 MoE GGUF is an open-source language model by TheBloke. Features: LLM, VRAM: 22.4GB, License: mit, MoE, Quantized, LLM Explorer Score: 0.11.

Base model:quantized:tomgrc/fu... Base model:tomgrc/fusionnet 34... Conversational En Gguf Mixtral Moe Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/FusionNet_34Bx2_MoE-GGUF

FusionNet 34Bx2 MoE GGUF Parameters and Internals

Model Type

mixtral

Additional Notes

Fine-tuned model on English language using MoE method. This model is fine-tuned to experiment with the MoE method, which could significantly increase performance.

LLM Name	FusionNet 34Bx2 MoE GGUF
Repository 🤗	https://huggingface.co/TheBloke/FusionNet_34Bx2_MoE-GGUF
Model Name	FusionNet 34Bx2 MoE
Model Creator	Suqin Zhang
Base Model(s)	FusionNet 34Bx2 MoE TomGrc/FusionNet_34Bx2_MoE
Required VRAM	22.4 GB
Updated	2026-06-29
Maintainer	TheBloke
Model Type	mixtral
Model Files	22.4 GB 31.8 GB 29.2 GB 26.3 GB 34.3 GB 36.7 GB 34.6 GB 41.9 GB 43.1 GB 41.9 GB 49.9 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	mit

Rank the FusionNet 34Bx2 MoE GGUF 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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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/FusionNet_34Bx2_MoE-GGUF.