What are the hardware requirements for Fimbulvetr 11B V2.8.0bpw H8 EXL2?

Fimbulvetr 11B V2.8.0bpw H8 EXL2 requires approximately 10.9 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Fimbulvetr 11B V2.8.0bpw H8 EXL2 and how large is it?

Fimbulvetr 11B V2.8.0bpw H8 EXL2 is developed by LoneStriker, 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 Fimbulvetr 11B V2.8.0bpw H8 EXL2?

Fimbulvetr 11B V2.8.0bpw H8 EXL2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Fimbulvetr 11B V2.8.0bpw H8 EXL2 by LoneStriker — VRAM 10.9GB, 4K context

Name: Fimbulvetr 11B V2.8.0bpw H8 EXL2
Author: LoneStriker

Fimbulvetr 11B V2.8.0bpw H8 EXL2 is an open-source language model by LoneStriker. Features: 11b LLM, VRAM: 10.9GB, Context: 4K, License: cc-by-nc-4.0, Quantized, LLM Explorer Score: 0.11.

En Endpoints compatible Exl2 Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/LoneStriker/Fimbulvetr-11B-v2-8.0bpw-h8-exl2

Fimbulvetr 11B V2.8.0bpw H8 EXL2 Parameters and Internals

Additional Notes

This description contains informal context about personal musings and challenges from the developer.

Supported Languages

en (unknown)

Input Output

Input Format:

Alpaca or Vicuna

Release Notes

Version:

15/2

Notes:

Suitable for Release. Model focused on the submission for the Chai app. Scaling results to Yi/Mixtral soon.

LLM Name	Fimbulvetr 11B V2.8.0bpw H8 EXL2
Repository 🤗	https://huggingface.co/LoneStriker/Fimbulvetr-11B-v2-8.0bpw-h8-exl2
Model Size	11b
Required VRAM	10.9 GB
Updated	2026-08-06
Maintainer	LoneStriker
Model Type	llama
Model Files	8.6 GB: 1-of-2 2.3 GB: 2-of-2
Supported Languages	en
Quantization Type	exl2
Model Architecture	LlamaForCausalLM
License	cc-by-nc-4.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.37.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Fimbulvetr 11B V2.8.0bpw H8 EXL2 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

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Fimbulvetr-11B-v2-8.0bpw-h8-exl2.