What are the hardware requirements for KafkaLM Mixtral 8x7B V0.2 DPO AWQ?

KafkaLM Mixtral 8x7B V0.2 DPO AWQ requires approximately 24.7 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 KafkaLM Mixtral 8x7B V0.2 DPO AWQ and how large is it?

KafkaLM Mixtral 8x7B V0.2 DPO AWQ is developed by doubledsbv, 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 KafkaLM Mixtral 8x7B V0.2 DPO AWQ?

KafkaLM Mixtral 8x7B V0.2 DPO AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

KafkaLM Mixtral 8x7B V0.2 DPO AWQ by doubledsbv — VRAM 24.7GB, 32K context

Name: KafkaLM Mixtral 8x7B V0.2 DPO AWQ
Author: doubledsbv

KafkaLM Mixtral 8x7B V0.2 DPO AWQ is an open-source language model by doubledsbv. Features: 46.7b LLM, VRAM: 24.7GB, Context: 32K, MoE, Quantized, Merged, LLM Explorer Score: 0.13.

Merged Model Arxiv:1910.09700 4-bit Awq Conversational Endpoints compatible Mixtral Moe Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/doubledsbv/KafkaLM-Mixtral-8x7B-V0.2_DPO-AWQ

KafkaLM Mixtral 8x7B V0.2 DPO AWQ Parameters and Internals

LLM Name	KafkaLM Mixtral 8x7B V0.2 DPO AWQ
Repository 🤗	https://huggingface.co/doubledsbv/KafkaLM-Mixtral-8x7B-V0.2_DPO-AWQ
Merged Model	Yes
Model Size	46.7b
Required VRAM	24.7 GB
Updated	2026-08-04
Maintainer	doubledsbv
Model Type	mixtral
Model Files	5.0 GB: 1-of-5 5.0 GB: 2-of-5 5.0 GB: 3-of-5 5.0 GB: 4-of-5 4.7 GB: 5-of-5
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MixtralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.40.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

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