What are the hardware requirements for GritLM 8x7B?

GritLM 8x7B requires approximately 93.6 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 GritLM 8x7B and how large is it?

GritLM 8x7B is developed by GritLM, a model with 46.7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does GritLM 8x7B perform on standard benchmarks?

GritLM 8x7B has the following published scores: MMLU 71.42. Compare against reference models on this page or on the LLM Explorer leaderboards.

GritLM 8x7B by GritLM — VRAM 93.6GB, 32K context

Name: GritLM 8x7B
Author: GritLM

GritLM 8x7B is an open-source language model by GritLM. Features: 46.7b LLM, VRAM: 93.6GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.15, Arc: 67.8, HellaSwag: 86.5, MMLU: 71.4, GSM8K: 61.6.

Arxiv:2402.09906 Base model:finetune:mistralai/... Base model:mistralai/mixtral-8... Conversational Custom code Dataset:gritlm/tulu2 Endpoints compatible Instruct Mixtral Model-index Moe Mteb Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/GritLM/GritLM-8x7B

GritLM 8x7B Parameters and Internals

LLM Name	GritLM 8x7B
Repository 🤗	https://huggingface.co/GritLM/GritLM-8x7B
Base Model(s)	mistralai/Mixtral-8x7B-Instruct-v0.1 mistralai/Mixtral-8x7B-Instruct-v0.1
Model Size	46.7b
Required VRAM	93.6 GB
Updated	2026-07-13
Maintainer	GritLM
Model Type	mixtral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-19 5.0 GB: 2-of-19 5.0 GB: 3-of-19 4.9 GB: 4-of-19 5.0 GB: 5-of-19 5.0 GB: 6-of-19 4.9 GB: 7-of-19 5.0 GB: 8-of-19 5.0 GB: 9-of-19 4.9 GB: 10-of-19 5.0 GB: 11-of-19 5.0 GB: 12-of-19 5.0 GB: 13-of-19 4.9 GB: 14-of-19 5.0 GB: 15-of-19 5.0 GB: 16-of-19 4.9 GB: 17-of-19 5.0 GB: 18-of-19 4.2 GB: 19-of-19 4.9 GB: 1-of-19 5.0 GB: 2-of-19 5.0 GB: 3-of-19 4.9 GB: 4-of-19 5.0 GB: 5-of-19 5.0 GB: 6-of-19 4.9 GB: 7-of-19 5.0 GB: 8-of-19 5.0 GB: 9-of-19 4.9 GB: 10-of-19 5.0 GB: 11-of-19 5.0 GB: 12-of-19 5.0 GB: 13-of-19 4.9 GB: 14-of-19 5.0 GB: 15-of-19 5.0 GB: 16-of-19 4.9 GB: 17-of-19 5.0 GB: 18-of-19 4.2 GB: 19-of-19
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the GritLM 8x7B 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 GritLM 8x7B

Model	Likes	Downloads	VRAM
GritLM 8x7B GGUF	4	129	17 GB

Best Alternatives to GritLM 8x7B

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x7B Instruct V0.1	32K / 93.6 GB	842893	4720
Mixtral 8x7B Instruct V0.1	32K / 93.6 GB	7	0
Mixtral 8x7B Instruct V0.1 FP8	32K / 47.1 GB	3383	0
Merge Mixtral Prometheus 8x7B	32K / 91.9 GB	12	2
...xtral 8x7B Yes Instruct LimaRP	32K / 93.5 GB	5	1
Notux 8x7b V1	32K / 93.6 GB	43	165
BagelMIsteryTour V2 8x7B	32K / 93.5 GB	94	17
...rkrautLM Mixtral 8x7B Instruct	32K / 93.6 GB	84	22
Mixtral 8x7B Instruct V0.1 FP8	32K / 47.1 GB	374	0
Sage Ft Mixtral 8x7b	32K / 90 GB	45	25

Note: green Score (e.g. "73.2") means that the model is better than GritLM/GritLM-8x7B.