What are the hardware requirements for Yi 70B 200K RPMerge Franken?

Yi 70B 200K RPMerge Franken requires approximately 142.4 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 Yi 70B 200K RPMerge Franken and how large is it?

Yi 70B 200K RPMerge Franken is developed by DisOOM, a model with 70b parameters. 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 Yi 70B 200K RPMerge Franken?

Yi 70B 200K RPMerge Franken is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Yi 70B 200K RPMerge Franken by DisOOM — VRAM 142.4GB, 195K context

Name: Yi 70B 200K RPMerge Franken
Author: DisOOM

Yi 70B 200K RPMerge Franken is an open-source language model by DisOOM. Features: 70b LLM, VRAM: 142.4GB, Context: 195K, License: other, LLM Explorer Score: 0.11.

Chat Chi Conversational En Endpoints compatible Llama Merge Mergekit Region:us Safetensors Sharded Tensorflow Yi

Model Card on HF 🤗: https://huggingface.co/DisOOM/Yi-70B-200k-RPMerge-Franken

Yi 70B 200K RPMerge Franken Parameters and Internals

Model Type

text generation, conversational

Additional Notes

This is a frankenmerge created by interleaving layers of the Yi-34B with itself to increase the parameter count and enhance performance.

Supported Languages

en (English), chi (Chinese)

Training Details

Methodology:

Interleaving layers of Yi-34B-200K-RPMerge with itself using mergekit

LLM Name	Yi 70B 200K RPMerge Franken
Repository 🤗	https://huggingface.co/DisOOM/Yi-70B-200k-RPMerge-Franken
Model Size	70b
Required VRAM	142.4 GB
Updated	2026-09-03
Maintainer	DisOOM
Model Type	llama
Model Files	9.6 GB: 1-of-15 9.7 GB: 2-of-15 9.9 GB: 3-of-15 9.9 GB: 4-of-15 9.9 GB: 5-of-15 9.9 GB: 6-of-15 9.8 GB: 7-of-15 9.9 GB: 8-of-15 9.8 GB: 9-of-15 9.8 GB: 10-of-15 10.0 GB: 11-of-15 9.7 GB: 12-of-15 10.0 GB: 13-of-15 10.0 GB: 14-of-15 4.5 GB: 15-of-15
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	other
Context Length	200000
Model Max Length	200000
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	64002
Torch Data Type	float16

Rank the Yi 70B 200K RPMerge Franken 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

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Note: green Score (e.g. "73.2") means that the model is better than DisOOM/Yi-70B-200k-RPMerge-Franken.