What are the hardware requirements for TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2?

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2 requires approximately 31.3 GB of VRAM and supports a context window of 195K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2?

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2 by LoneStriker — VRAM 31.3GB, 195K context

Name: TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2
Author: LoneStriker

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2 is an open-source language model by LoneStriker. Features: LLM, VRAM: 31.3GB, Context: 195K, License: other, MoE, Quantized, LLM Explorer Score: 0.11.

Autotrain compatible Conversational Endpoints compatible Exl2 Fp16 Mixtral Moe Quantized Region:us Safetensors Sharded Tensorflow Yi

Model Card on HF 🤗: https://huggingface.co/LoneStriker/TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO_f16-4.0bpw-h6-exl2

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2 Parameters and Internals

Model Type

multimodal

Training Details

Methodology:

DPO Trainer TRL supports the DPO Trainer for training language models from preference data, as described in the paper Direct Preference Optimization by Rafailov et al., 2023.

LLM Name	TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2
Repository 🤗	https://huggingface.co/LoneStriker/TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO_f16-4.0bpw-h6-exl2
Required VRAM	31.3 GB
Updated	2025-09-23
Maintainer	LoneStriker
Model Type	mixtral
Model Files	8.6 GB: 1-of-4 8.6 GB: 2-of-4 8.6 GB: 3-of-4 5.5 GB: 4-of-4
Quantization Type	fp16\|exl2
Model Architecture	MixtralForCausalLM
License	other
Context Length	200000
Model Max Length	200000
Transformers Version	4.37.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	64000
Torch Data Type	bfloat16

Rank the TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 4.0bpw H6 EXL2

Best Alternatives	Context / RAM	Downloads	Likes
...oE V0.1 DPO F16 5.0bpw H6 EXL2	195K / 38.8 GB	6	0
...2 Mixtral 8x22b 6.0bpw H8 EXL2	64K / 105.8 GB	2	1
WizardLM 2 8x22 EXL2 4.0bpw	64K / 70.9 GB	7	1
...M 2 8x22B Beige 5.0bpw H6 EXL2	64K / 88.5 GB	8	0
...M 2 8x22B Beige 4.0bpw H6 EXL2	64K / 70.8 GB	6	0
...M 2 8x22B Beige 2.4bpw H6 EXL2	64K / 42.7 GB	5	0
...M 2 8x22B Beige 3.0bpw H6 EXL2	64K / 53.2 GB	5	0
...rdLM 2 8x22B Beige EXL2 5.0bpw	64K / 88.4 GB	5	0
...B Instruct V0.1 8.0bpw H8 EXL2	64K / 120.2 GB	6	1
...2 Mixtral 8x22b 8.0bpw H8 EXL2	64K / 125.1 GB	11	2

Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO_f16-4.0bpw-h6-exl2.