What are the hardware requirements for Neural Chat 7B V3.3 GPTQ?

Neural Chat 7B V3.3 GPTQ requires approximately 4.2 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 Neural Chat 7B V3.3 GPTQ and how large is it?

Neural Chat 7B V3.3 GPTQ is developed by TheBloke, a model with 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 Neural Chat 7B V3.3 GPTQ?

Neural Chat 7B V3.3 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Neural Chat 7B V3.3 GPTQ by TheBloke — VRAM 4.2GB, 32K context

Name: Neural Chat 7B V3.3 GPTQ
Author: TheBloke

Neural Chat 7B V3.3 GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

4-bit Base model:intel/neural-chat-7... Base model:quantized:intel/neu... Gptq Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/neural-chat-7B-v3-3-GPTQ

Neural Chat 7B V3.3 GPTQ Parameters and Internals

Model Type

mistral

Use Cases

Applications:

Language-related tasks inference

Limitations:

Model should be fine-tuned for specific tasks; cannot be used to create hostile environments

Additional Notes

Know compatible clients/servers available for running models inferences.

Training Details

Data Sources:

meta-math/MetaMathQA, Intel/orca_dpo_pairs

Methodology:

Aligned using Direct Performance Optimization (DPO) method

Hardware Used:

Intel Gaudi 2 processor

Model Architecture:

Fine-tuned from Mistral-7B-v-0.1

Input Output

Input Format:

### System: {system_message} ### User: {prompt} ### Assistant:

Accepted Modalities:

text

LLM Name	Neural Chat 7B V3.3 GPTQ
Repository 🤗	https://huggingface.co/TheBloke/neural-chat-7B-v3-3-GPTQ
Model Name	Neural Chat 7B V3-3
Model Creator	Intel
Base Model(s)	Neural Chat 7B V3.3 Intel/neural-chat-7b-v3-3
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-06-26
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Neural Chat 7B V3.3 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

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...enHermes 2.5 Mistral 7B Marlin	32K / 4.1 GB	6	2
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...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	2946	18
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...istral 7B Pruned50 GPTQ Marlin	32K / 4 GB	5	0
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Mistral 7B Unsloth Gptq 8bit	32K / 7.7 GB	7	0
Cosmosage V2	32K / 4.2 GB	8	4
...phyr 7B Beta Assistant V1 Gptq	32K / 4.2 GB	2	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/neural-chat-7B-v3-3-GPTQ.