What are the hardware requirements for LUNA SOLARkrautLM Instruct?

LUNA SOLARkrautLM Instruct requires approximately 21.4 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 LUNA SOLARkrautLM Instruct and how large is it?

LUNA SOLARkrautLM Instruct is developed by fblgit, 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.

How does LUNA SOLARkrautLM Instruct perform on standard benchmarks?

LUNA SOLARkrautLM Instruct has the following published scores: MMLU 66.11. Compare against reference models on this page or on the LLM Explorer leaderboards.

LUNA SOLARkrautLM Instruct by fblgit — VRAM 21.4GB, 4K context

Name: LUNA SOLARkrautLM Instruct
Author: fblgit

LUNA SOLARkrautLM Instruct is an open-source language model by fblgit. Features: 10.7b LLM, VRAM: 21.4GB, Context: 4K, License: cc-by-nc-4.0, Instruction-Based, LLM Explorer Score: 0.11, Arc: 71.2, HellaSwag: 88.3, MMLU: 66.1, GSM8K: 60.9.

Augmentation Conversational Dataset:argilla/distilabel-mat... De Doi:10.57967/hf/1517 Dpo En Endpoints compatible Finetuned German Instruct Llama Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/fblgit/LUNA-SOLARkrautLM-Instruct

LUNA SOLARkrautLM Instruct Parameters and Internals

Model Type

LUNA-SOLARkrautLM-Instruct, text-generation

Use Cases

Areas:

research, commercial applications

Additional Notes

Despite data cleansing, uncensored content may still occur.

Supported Languages

English (Yes), German (Yes)

Training Details

Data Sources:

SauerkrautLM-DPO, argilla/distilabel-math-preference-dpo, HuggingFaceH4/ultrafeedback_binarized

Methodology:

Aligned through DPO with German data augmentation. Translated data was used and unnatural phrasings were corrected using data augmentation techniques.

LLM Name	LUNA SOLARkrautLM Instruct
Repository 🤗	https://huggingface.co/fblgit/LUNA-SOLARkrautLM-Instruct
Model Size	10.7b
Required VRAM	21.4 GB
Updated	2026-08-06
Maintainer	fblgit
Model Type	llama
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-5 5.0 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 1.7 GB: 5-of-5
Supported Languages	en de
Model Architecture	LlamaForCausalLM
License	cc-by-nc-4.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the LUNA SOLARkrautLM Instruct 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 LUNA SOLARkrautLM Instruct

Model	Likes	Downloads	VRAM
...UNA SOLARkrautLM Instruct GGUF	4	924	4 GB
...UNA SOLARkrautLM Instruct GPTQ	2	8	6 GB
LUNA SOLARkrautLM Instruct AWQ	0	7	6 GB

Best Alternatives to LUNA SOLARkrautLM Instruct

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
SauerkrautLM SOLAR Instruct	8K / 21.4 GB	62	46
MetaModelv2	8K / 21.4 GB	197	0
Kazemi 1.2 Solar	8K / 21.4 GB	0	0
Solarmer3	4K / 21.4 GB	5	0
Somer2	4K / 21.4 GB	10	0
SOLAR 10.7B Instruct V1.0	4K / 21.4 GB	53386	657
SOLAR 10.7B Instruct V1.0	4K / 21.4 GB	17	0
Somer	4K / 21.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than fblgit/LUNA-SOLARkrautLM-Instruct.