What are the hardware requirements for Hiber Multi 10B Instruct?

Hiber Multi 10B 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 Hiber Multi 10B Instruct and how large is it?

Hiber Multi 10B Instruct is developed by Hibernates, a model with 8b 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 Hiber Multi 10B Instruct?

Hiber Multi 10B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Hiber Multi 10B Instruct by Hibernates — VRAM 21.4GB, 4K context

Name: Hiber Multi 10B Instruct
Author: Hibernates

Hiber Multi 10B Instruct is an open-source language model by Hibernates. Features: 8b LLM, VRAM: 21.4GB, Context: 4K, License: llama3.1, Instruction-Based, LLM Explorer Score: 0.17.

Base model:finetune:meta-llama... Base model:meta-llama/llama-3.... Conversational De En Endpoints compatible Es Flash-attention2 Fr Hiber-multi Instruct Ja Ko Llama Llama3.1 Multilingual-llm Quantization Region:us Ru Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/Hibernates/Hiber-Multi-10B-Instruct

Hiber Multi 10B Instruct Parameters and Internals

LLM Name	Hiber Multi 10B Instruct
Repository 🤗	https://huggingface.co/Hibernates/Hiber-Multi-10B-Instruct
Base Model(s)	meta-llama/Llama-3.1-8B-Instruct meta-llama/Llama-3.1-8B-Instruct
Model Size	8b
Required VRAM	21.4 GB
Updated	2026-08-05
Maintainer	Hibernates
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 zh es fr de ja ko ru
Model Architecture	LlamaForCausalLM
License	llama3.1
Context Length	4096
Model Max Length	4096
Transformers Version	4.47.1
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Hiber Multi 10B Instruct capabilities

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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 Hiber Multi 10B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
...otron 8B UltraLong 4M Instruct	4192K / 32.1 GB	1135	125
UltraLong Thinking	4192K / 16.1 GB	2	3
...a 3.1 8B UltraLong 4M Instruct	4192K / 32.1 GB	176	24
...a 3.1 8B UltraLong 2M Instruct	2096K / 32.1 GB	875	9
...otron 8B UltraLong 2M Instruct	2096K / 32.1 GB	124	18
Cthulhu 8B V1.4	1048K / 16.1 GB	10	10
...raLong 1M Instruct Abliterated	1048K / 32.1 GB	4	9
...a 3.1 8B UltraLong 1M Instruct	1048K / 32.1 GB	1387	29
...otron 8B UltraLong 1M Instruct	1048K / 32.1 GB	702	59
Zero Llama 3.1 8B Beta6	1048K / 16.1 GB	7	1

Note: green Score (e.g. "73.2") means that the model is better than Hibernates/Hiber-Multi-10B-Instruct.