What are the hardware requirements for Mistral Ft Optimized 1218 GPTQ?

Mistral Ft Optimized 1218 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 Mistral Ft Optimized 1218 GPTQ and how large is it?

Mistral Ft Optimized 1218 GPTQ 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 1218 GPTQ?

Mistral Ft Optimized 1218 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Ft Optimized 1218 GPTQ by TheBloke — VRAM 4.2GB, 32K context

Name: Mistral Ft Optimized 1218 GPTQ
Author: TheBloke

Mistral Ft Optimized 1218 GPTQ 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 Base model:openpipe/mistral-ft... Base model:quantized:openpipe/... En Gptq Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/mistral-ft-optimized-1218-GPTQ

Mistral Ft Optimized 1218 GPTQ Parameters and Internals

Model Type

mistral

Additional Notes

This model is intended to be a strong base suitable for downstream fine-tuning on a variety of tasks. Based on internal evaluations, it's considered one of the strongest models for most downstream tasks.

Supported Languages

en (high)

Input Output

Input Format:

{prompt}

LLM Name	Mistral Ft Optimized 1218 GPTQ
Repository 🤗	https://huggingface.co/TheBloke/mistral-ft-optimized-1218-GPTQ
Model Name	Mistral FT Optimized 1218
Model Creator	OpenPipe
Base Model(s)	Mistral Ft Optimized 1218 OpenPipe/mistral-ft-optimized-1218
Model Size	7.2b
Required VRAM	4.2 GB
Updated	2026-08-05
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mistral Ft Optimized 1218 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 Mistral Ft Optimized 1218 GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Multi Verse Model GPTQ	32K / 4.2 GB	111	1
Garrulus GPTQ	32K / 4.2 GB	28	3
HamSter 0.1 GPTQ	32K / 4.2 GB	7	2
Phoenix GPTQ	32K / 4.2 GB	12	1
Mistral Ft Optimized 1227 GPTQ	32K / 4.2 GB	19	2
...hat 3.5 1210 Seraph Slerp GPTQ	32K / 4.2 GB	10	2
...h Openchat 3.5 1210 Slerp GPTQ	32K / 4.2 GB	6	1
Metis 0.5 GPTQ	32K / 4.2 GB	6	1
XDAN L1 Chat RL V1 GPTQ	32K / 4.2 GB	15	3
Apricot Wildflower 20 GPTQ	32K / 4.2 GB	12	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/mistral-ft-optimized-1218-GPTQ.