What are the hardware requirements for MetaMath Mistral 7B GGUF?

MetaMath Mistral 7B GGUF requires approximately 3.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MetaMath Mistral 7B GGUF and how large is it?

MetaMath Mistral 7B GGUF 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 MetaMath Mistral 7B GGUF?

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

MetaMath Mistral 7B GGUF by TheBloke — VRAM 3.1GB

Name: MetaMath Mistral 7B GGUF
Author: TheBloke

MetaMath Mistral 7B GGUF is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.1GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

Arxiv:2309.12284 Arxiv:2310.06825 Base model:meta-math/metamath-... Base model:quantized:meta-math... Dataset:meta-math/metamathqa Gguf Mistral Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/MetaMath-Mistral-7B-GGUF

MetaMath Mistral 7B GGUF Parameters and Internals

Model Type

mistral

Additional Notes

Quantized using hardware provided by Massed Compute. Compatible with various libraries and interfaces using the GGUF format.

Training Details

Data Sources:

MetaMathQA datasets

Methodology:

Fine-tuning Mistral-7B with a smaller learning rate

Input Output

Input Format:

Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {prompt} ### Response:

LLM Name	MetaMath Mistral 7B GGUF
Repository 🤗	https://huggingface.co/TheBloke/MetaMath-Mistral-7B-GGUF
Model Name	Metamath Mistral 7B
Model Creator	MetaMath
Base Model(s)	MetaMath Mistral 7B meta-math/MetaMath-Mistral-7B
Model Size	7b
Required VRAM	3.1 GB
Updated	2026-08-07
Maintainer	TheBloke
Model Type	mistral
Model Files	3.1 GB 3.8 GB 3.5 GB 3.2 GB 4.1 GB 4.4 GB 4.1 GB 5.0 GB 5.1 GB 5.0 GB 5.9 GB 7.7 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the MetaMath Mistral 7B GGUF 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 MetaMath Mistral 7B GGUF

Best Alternatives	Context / RAM	Downloads	Likes
Pixel	8K / 4.4 GB	17	0
Qwen2 7B Alpacha Q8 0	0K / 9.1 GB	23	0
...ral 7B Instruct V0.2 Llamafile	0K / 14.5 GB	8850	25
Conversely Mistral 7B	0K / 0.2 GB	132	0
Mistral 7B Instruct V0.3 GGUF	0K / 1.6 GB	91691	147
CleverBoi 7B V2	0K / 0.1 GB	586	0
WizardLM 2 7B GGUF	0K / 2.7 GB	93547	83
Qwen2 7B Instruct GGUF	0K / 1.9 GB	56414	10
...hemeng Qwen Math 7b 24 1 100 1	0K / 15.2 GB	25	0
Mistral 7B Instruct V0.2 GGUF	0K / 3.1 GB	70243	511

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/MetaMath-Mistral-7B-GGUF.