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

Neural Chat 7B V3.3 requires approximately 14.4 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 and how large is it?

Neural Chat 7B V3.3 is developed by Intel, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Neural Chat 7B V3.3 perform on standard benchmarks?

Neural Chat 7B V3.3 has the following published scores: MMLU 63.07. Compare against reference models on this page or on the LLM Explorer leaderboards.

Neural Chat 7B V3.3 by Intel — VRAM 14.4GB, 32K context

Name: Neural Chat 7B V3.3
Author: Intel

Neural Chat 7B V3.3 is an open-source language model by Intel. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.21, Arc: 66.9, HellaSwag: 85.3, MMLU: 63.1, GSM8K: 61.1.

Arxiv:2309.12284 Base model:finetune:intel/neur... Base model:intel/neural-chat-7... Conversational Deploy:azure Endpoints compatible Intel Math Mistral Model-index Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Intel/neural-chat-7b-v3-3

Neural Chat 7B V3.3 Parameters and Internals

Model Type

Large Language Model

Use Cases

Areas:

Research, Commercial applications

Applications:

Inference on language-related tasks

Primary Use Cases:

Language-related tasks

Limitations:

May produce factually incorrect or biased outputs, requires fine-tuning for specific tasks

Additional Notes

The model should not be used to intentionally create hostile or alienating environments.

Training Details

Data Sources:

meta-math/MetaMathQA

Methodology:

Aligned using Direct Performance Optimization (DPO) method with Intel/orca_dpo_pairs

Context Length:

8192

Hardware Used:

Intel Gaudi 2 processor (8 cards)

Model Architecture:

Fine-tuned 7B parameter LLM on the Intel Gaudi 2 processor

Safety Evaluation

Methodologies:

Safety testing before deployment

Ethical Considerations:

Can produce factually incorrect output and biases, risk of generating offensive outputs. Developers should perform safety testing.

Input Output

Performance Tips:

Model performance varies based on inputs.

LLM Name	Neural Chat 7B V3.3
Repository 🤗	https://huggingface.co/Intel/neural-chat-7b-v3-3
Base Model(s)	Neural Chat 7B V3.1 Intel/neural-chat-7b-v3-1
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-04
Maintainer	Intel
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2 9.9 GB: 1-of-2 4.5 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.34.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Neural Chat 7B V3.3 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

Quantized Models of the Neural Chat 7B V3.3

Model	Likes	Downloads	VRAM
Neural Chat 7B V3.3 GGUF	0	254	3 GB
Neural Chat 7B V3.3 GPTQ	1	2	4 GB
Neural Chat 7B V3.3 GGUF	14	341	3 GB
Neural Chat 7B V3.3 GPTQ	3	54	4 GB
Neural Chat 7B V3.3 AWQ	0	26	4 GB

Best Alternatives to Neural Chat 7B V3.3

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

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