What are the hardware requirements for Open Gpt4 8x7B V0.2 GPTQ?

Open Gpt4 8x7B V0.2 GPTQ requires approximately 23.8 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Open Gpt4 8x7B V0.2 GPTQ and how large is it?

Open Gpt4 8x7B V0.2 GPTQ is developed by TheBloke, a model with 46.7b 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 Open Gpt4 8x7B V0.2 GPTQ?

Open Gpt4 8x7B V0.2 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Open Gpt4 8x7B V0.2 GPTQ by TheBloke — VRAM 23.8GB, 32K context

Name: Open Gpt4 8x7B V0.2 GPTQ
Author: TheBloke

Open Gpt4 8x7B V0.2 GPTQ is an open-source language model by TheBloke. Features: 46.7b LLM, VRAM: 23.8GB, Context: 32K, License: apache-2.0, MoE, Quantized, LLM Explorer Score: 0.1.

4-bit Base model:quantized:rombodawg... Base model:rombodawg/open gpt4... Gptq Merge Mixtral Moe Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Open_Gpt4_8x7B_v0.2-GPTQ

Open Gpt4 8x7B V0.2 GPTQ Parameters and Internals

Model Type

mixtral

Additional Notes

This model is aimed to be even more competitive with closed source models like Gpt-4 through community testing. Multiple quantization options are provided for various requirements and hardware configurations. The model is available in unquantized fp16 for further conversions.

Training Details

Methodology:

TIES merger of Mixtral-8x7B-Instruct-v0.1 and bagel-dpo-8x7b-v0.2 with MixtralOrochi8x7B as the Base model.

Input Output

Input Format:

Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {prompt} ### Response:

LLM Name	Open Gpt4 8x7B V0.2 GPTQ
Repository 🤗	https://huggingface.co/TheBloke/Open_Gpt4_8x7B_v0.2-GPTQ
Model Name	Open Gpt4 8X7B V0.2
Model Creator	rombo dawg
Base Model(s)	rombodawg/Open_Gpt4_8x7B_v0.2 rombodawg/Open_Gpt4_8x7B_v0.2
Model Size	46.7b
Required VRAM	23.8 GB
Updated	2026-08-01
Maintainer	TheBloke
Model Type	mixtral
Model Files	23.8 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Open Gpt4 8x7B V0.2 GPTQ 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 Open Gpt4 8x7B V0.2 GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x7B V0.1 GPTQ	32K / 23.8 GB	181	126
...ixtral 8x7B Instruct V0.1 GPTQ	32K / 23.8 GB	210	141
...Hermes 2 Mixtral 8x7B DPO GPTQ	32K / 23.8 GB	31	26
...Hermes 2 Mixtral 8x7B SFT GPTQ	32K / 23.8 GB	10	11
Dolphin 2.5 Mixtral 8x7b GPTQ	32K / 23.8 GB	81	114
Bagel DPO 8x7b V0.2 GPTQ	32K / 23.8 GB	12	2
...xtral Instruct 8x7b Zloss GPTQ	32K / 23.8 GB	7	2
Sensualize Mixtral GPTQ	32K / 23.8 GB	9	5
....1 LimaRP ZLoss DARE TIES GPTQ	32K / 23.8 GB	5	6
Dolphin 2.7 Mixtral 8x7b GPTQ	32K / 23.8 GB	32	19

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Open_Gpt4_8x7B_v0.2-GPTQ.