What are the hardware requirements for Mistral Ft Optimized 1227 AWQ?

Mistral Ft Optimized 1227 AWQ 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 Mistral Ft Optimized 1227 AWQ and how large is it?

Mistral Ft Optimized 1227 AWQ is developed by TheBloke, a model with 7.2b 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 Mistral Ft Optimized 1227 AWQ?

Mistral Ft Optimized 1227 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Ft Optimized 1227 AWQ by TheBloke — VRAM 4.2GB, 32K context

Name: Mistral Ft Optimized 1227 AWQ
Author: TheBloke

Mistral Ft Optimized 1227 AWQ is an open-source language model by TheBloke. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

4-bit Awq Base model:openpipe/mistral-ft... Base model:quantized:openpipe/... Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/mistral-ft-optimized-1227-AWQ

Mistral Ft Optimized 1227 AWQ Parameters and Internals

Model Type

mistral

Additional Notes

The model is an AWQ quantized version, offering efficient low-bit weight quantization for better inference speed while maintaining accuracy.

LLM Name	Mistral Ft Optimized 1227 AWQ
Repository 🤗	https://huggingface.co/TheBloke/mistral-ft-optimized-1227-AWQ
Model Name	Mistral FT Optimized 1227
Model Creator	OpenPipe
Base Model(s)	Mistral Ft Optimized 1227 OpenPipe/mistral-ft-optimized-1227
Model Size	7.2b
Required VRAM	4.2 GB
Updated	2026-08-05
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral Ft Optimized 1227 AWQ capabilities

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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 Mistral Ft Optimized 1227 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Feedback Wizard 4bit AWQ	32K / 4.2 GB	6	0
Ryze AWQ 4bit	32K / 4.2 GB	5	0
...V3 Plot Chat Roleplay Chat AWQ	32K / 4.2 GB	7	0
...lot Engine Step Json Short AWQ	32K / 4.2 GB	5	0
MistralLite AWQ	32K / 4.2 GB	27	6
LemonadeRP 4.5.3 AWQ	32K / 4.2 GB	5	0
Functionary Small V2.4 AWQ	32K / 4.2 GB	1	1
Hc Mistral Alpaca Merged AWQ	32K / 4.2 GB	5	0
Garrulus AWQ	32K / 4.2 GB	7	2
HamSter 0.1 AWQ	32K / 4.2 GB	5	2

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/mistral-ft-optimized-1227-AWQ.