What are the hardware requirements for Fimbulvetr V2 Kuro Lotus Bf16?

Fimbulvetr V2 Kuro Lotus Bf16 requires approximately 21.5 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Fimbulvetr V2 Kuro Lotus Bf16 and how large is it?

Fimbulvetr V2 Kuro Lotus Bf16 is developed by gelukuMLG, a model with 10.7b 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 Fimbulvetr V2 Kuro Lotus Bf16?

Fimbulvetr V2 Kuro Lotus Bf16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Fimbulvetr V2 Kuro Lotus Bf16 by gelukuMLG — VRAM 21.5GB, 8K context

Name: Fimbulvetr V2 Kuro Lotus Bf16
Author: gelukuMLG

Fimbulvetr V2 Kuro Lotus Bf16 is an open-source language model by gelukuMLG. Features: 10.7b LLM, VRAM: 21.5GB, Context: 8K, Merged, LLM Explorer Score: 0.11.

Merged Model Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/gelukuMLG/Fimbulvetr-V2-Kuro-Lotus-bf16

Fimbulvetr V2 Kuro Lotus Bf16 Parameters and Internals

Additional Notes

This is a merge of pre-trained language models created using the mergekit tool.

Training Details

Methodology:

SLERP merge method

LLM Name	Fimbulvetr V2 Kuro Lotus Bf16
Repository 🤗	https://huggingface.co/gelukuMLG/Fimbulvetr-V2-Kuro-Lotus-bf16
Merged Model	Yes
Model Size	10.7b
Required VRAM	21.5 GB
Updated	2026-07-23
Maintainer	gelukuMLG
Model Type	llama
Model Files	1.0 GB: 1-of-22 0.9 GB: 2-of-22 0.9 GB: 3-of-22 1.0 GB: 4-of-22 1.0 GB: 5-of-22 1.0 GB: 6-of-22 1.0 GB: 7-of-22 1.0 GB: 8-of-22 0.9 GB: 9-of-22 1.0 GB: 10-of-22 1.0 GB: 11-of-22 1.0 GB: 12-of-22 0.9 GB: 13-of-22 1.0 GB: 14-of-22 1.0 GB: 15-of-22 1.0 GB: 16-of-22 0.9 GB: 17-of-22 1.0 GB: 18-of-22 1.0 GB: 19-of-22 1.0 GB: 20-of-22 1.0 GB: 21-of-22 1.0 GB: 22-of-22
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Fimbulvetr V2 Kuro Lotus Bf16 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 Fimbulvetr V2 Kuro Lotus Bf16

Best Alternatives	Context / RAM	Downloads	Likes
SOLAR 10.7B Instruct V1.0 128K	128K / 21.4 GB	57	3
SOLAR 10.7B V1.0 Instruct 16K	16K / 21.4 GB	63	2
SOLAR 10.7B V1.0 Base 16K	16K / 21.4 GB	69	0
SauerkrautLM SOLAR Instruct	8K / 21.4 GB	62	46
PiVoT SOLAR 10.7B RP	8K / 21.4 GB	54	7
MetaModelv2	8K / 21.4 GB	197	0
Kazemi 1.2 Solar	8K / 21.4 GB	0	0
Bucharest 0.2	5K / 21.4 GB	6	1
Solarmer3	4K / 21.4 GB	5	0
Somer2	4K / 21.4 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than gelukuMLG/Fimbulvetr-V2-Kuro-Lotus-bf16.