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

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 requires approximately 121.8 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.

Who developed TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 and how large is it?

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 is developed by cloudyu, a model with 60.8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 perform on standard benchmarks?

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 has the following published scores: MMLU 76.65. Compare against reference models on this page or on the LLM Explorer leaderboards.

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 by cloudyu — VRAM 121.8GB, 195K context

Name: TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16
Rating: 2 (2 reviews)
Author: cloudyu

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 is an open-source language model by cloudyu. Features: 60.8b LLM, VRAM: 121.8GB, Context: 195K, License: apache-2.0, MoE, Quantized, LLM Explorer Score: 0.14, Arc: 74.1, HellaSwag: 86.7, MMLU: 76.7, GSM8K: 74.5.

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

Model Card on HF 🤗: https://huggingface.co/cloudyu/TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO_f16

TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16 Parameters and Internals

Model Type

MoE, language model

LLM Name	TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16
Repository 🤗	https://huggingface.co/cloudyu/TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO_f16
Model Size	60.8b
Required VRAM	121.8 GB
Updated	2026-08-03
Maintainer	cloudyu
Model Type	mixtral
Model Files	4.9 GB: 1-of-25 4.8 GB: 2-of-25 4.9 GB: 3-of-25 4.8 GB: 4-of-25 4.9 GB: 5-of-25 4.8 GB: 6-of-25 4.9 GB: 7-of-25 5.0 GB: 8-of-25 5.0 GB: 9-of-25 5.0 GB: 10-of-25 5.0 GB: 11-of-25 5.0 GB: 12-of-25 5.0 GB: 13-of-25 5.0 GB: 14-of-25 5.0 GB: 15-of-25 5.0 GB: 16-of-25 5.0 GB: 17-of-25 5.0 GB: 18-of-25 5.0 GB: 19-of-25 5.0 GB: 20-of-25 5.0 GB: 21-of-25 5.0 GB: 22-of-25 5.0 GB: 23-of-25 5.0 GB: 24-of-25 2.8 GB: 25-of-25
Quantization Type	fp16
Model Architecture	MixtralForCausalLM
License	apache-2.0
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 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

Best Alternatives to TomGrc FusionNet 34Bx2 MoE V0.1 DPO F16

Best Alternatives	Context / RAM	Downloads	Likes
60B MoE Coder V3	195K / 121.8 GB	70	3
Mixtral 34Bx2 MoE 60B	195K / 121.9 GB	7876	114
Yi 34Bx2 MoE 60B DPO	195K / 121.8 GB	8035	3
Bagel Hermes 2x34B	195K / 121.9 GB	70	16
Yi 34Bx2 MoE 200K	195K / 121.9 GB	7897	2
Yi 34Bx2 MoE 60B	195K / 121.9 GB	7954	64
...34Bx2 MoE V0.1 Full Linear DPO	195K / 121.8 GB	68	2
FusionNet 34Bx2 MoE V0.1	195K / 121.2 GB	52	8
... Cloudyu Mixtral 34Bx2 MoE 60B	195K / 121.8 GB	57	0
Mixtral 34Bx2 MoE 60B GPTQ	195K / 31.8 GB	50	7

Note: green Score (e.g. "73.2") means that the model is better than cloudyu/TomGrc_FusionNet_34Bx2_MoE_v0.1_DPO_f16.