What are the hardware requirements for MistralLite 7B GPTQ?

MistralLite 7B 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 MistralLite 7B GPTQ and how large is it?

MistralLite 7B 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 MistralLite 7B GPTQ?

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

MistralLite 7B GPTQ by TheBloke — VRAM 4.2GB, 32K context

Name: MistralLite 7B GPTQ
Author: TheBloke

MistralLite 7B 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: 0.09.

4-bit Base model:amazon/mistrallite Base model:quantized:amazon/mi... Gptq Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/MistralLite-7B-GPTQ

MistralLite 7B GPTQ Parameters and Internals

Model Type

mistral

Use Cases

Areas:

Long context line and topic retrieval, Summarization, Question-answering

Additional Notes

MistralLite is fine-tuned from Mistral-7B-v0.1 with enhanced performance on long context processing, maintaining simple model structure.

Supported Languages

English (native)

Training Details

Data Sources:

SLidingEncoder and Decoder (SLED), (Long) Natural Questions (NQ), OpenAssistant Conversations Dataset (OASST1)

Methodology:

Enhanced capabilities of processing long context with adapted Rotary Embedding and sliding window during fine-tuning.

Context Length:

32000

Model Architecture:

Derived from Mistral-7B-v0.1 with an adapted Rotary Embedding and sliding window for better long context processing.

Input Output

Input Format:

<|prompter|>{prompt}~~<|assistant|>

Accepted Modalities:

text

LLM Name	MistralLite 7B GPTQ
Repository 🤗	https://huggingface.co/TheBloke/MistralLite-7B-GPTQ
Model Name	MistralLite 7B
Model Creator	Amazon Web Services
Base Model(s)	MistralLite amazon/MistralLite
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-07-07
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	4.34.0
Tokenizer Class	LlamaTokenizer
Padding Token	[PAD]
Vocabulary Size	32003
Torch Data Type	float16

Rank the MistralLite 7B 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 MistralLite 7B GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
...enHermes 2.5 Mistral 7B Marlin	32K / 4.1 GB	6	2
Zephyr 7B Beta Marlin	32K / 4.1 GB	16	0
Mistral 7B Instruct V0.3 GPTQ	32K / 4.2 GB	113881	1
...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	2946	18
...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	2658	25
Cosmosage V2	32K / 4.2 GB	8	4
...istral 7B Pruned50 GPTQ Marlin	32K / 4 GB	5	0
Mistral 7B Unsloth Gptq 8bit	32K / 7.7 GB	7	0
Mistral 7B Instruct V0.2 GPTQ	32K / 4.2 GB	6743	56
...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/MistralLite-7B-GPTQ.