What are the hardware requirements for Normistral 11B Warm?

Normistral 11B Warm requires approximately 22.9 GB of VRAM and supports a context window of 1000K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Normistral 11B Warm and how large is it?

Normistral 11B Warm is developed by norallm, a model with 11b 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 Normistral 11B Warm?

Normistral 11B Warm is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Normistral 11B Warm by norallm — VRAM 22.9GB, 1000K context

Name: Normistral 11B Warm
Author: norallm

Normistral 11B Warm is an open-source language model by norallm. Features: 11b LLM, VRAM: 22.9GB, Context: 1000K, License: apache-2.0, Quantized, LLM Explorer Score: 0.15.

Arxiv:2412.06484 Base model:mistralai/mistral-n... Base model:quantized:mistralai... Bokmaal Da En Endpoints compatible Fo Gguf Is Mistral Nb Nn No Norwegian Nynorsk Pytorch Quantized Region:us Safetensors Sami Se Sharded Sv Tensorflow

Model Card on HF 🤗: https://huggingface.co/norallm/normistral-11b-warm

Normistral 11B Warm Parameters and Internals

LLM Name	Normistral 11B Warm
Repository 🤗	https://huggingface.co/norallm/normistral-11b-warm
Base Model(s)	Mistral Nemo Base 2407 mistralai/Mistral-Nemo-Base-2407
Model Size	11b
Required VRAM	22.9 GB
Updated	2026-08-03
Maintainer	norallm
Model Type	mistral
Model Files	4.6 GB: 1-of-5 4.7 GB: 2-of-5 4.6 GB: 3-of-5 4.7 GB: 4-of-5 4.3 GB: 5-of-5 5.6 GB 6.9 GB 8.1 GB 9.4 GB 12.1 GB 22.9 GB
Supported Languages	nb nn no se sv da en is fo
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.44.0.dev0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	51200
Torch Data Type	bfloat16

Rank the Normistral 11B Warm 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 Normistral 11B Warm

Best Alternatives	Context / RAM	Downloads	Likes
Huginn V5.10.7B	32K / 21.4 GB	0	0
... 11B V2.2 Instruct EXL2 4.5bit	32K / 6.5 GB	391	3
...B V2.2 Instruct HQQ 8bit 128gs	32K / 11.7 GB	48	3
...B V2.2 Instruct HQQ 4bit 128gs	32K / 6.2 GB	43	3
...t 3.1 Frankenmerge 11B Gguf Q8	32K / 8.3 GB	65	1
Bielik 11B V2.2 Instruct GPTQ	32K / 6.2 GB	220	3
... 11B V2.2 Instruct Quanto 8bit	32K / 12 GB	209	4
Bielik 11B V2.2 Instruct W8A8	32K / 11.5 GB	172	3
Bielik 11B V2.2 Instruct AWQ	32K / 6.2 GB	85	3
Bielik 11B V2.2 Instruct FP8	32K / 11.4 GB	53	3

Note: green Score (e.g. "73.2") means that the model is better than norallm/normistral-11b-warm.