What are the hardware requirements for Ether0?

Ether0 requires approximately 95.3 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ether0 and how large is it?

Ether0 is developed by futurehouse, a model with 24b 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 Ether0?

Ether0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ether0 by futurehouse — VRAM 95.3GB, 32K context

Name: Ether0
Author: futurehouse

Ether0 is an open-source language model by futurehouse. Features: 24b LLM, VRAM: 95.3GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.19.

Arxiv:2506.17238 Base model:finetune:mistralai/... Base model:mistralai/mistral-s... Chemistry Conversational Dataset:futurehouse/ether0-ben... En Instruct Mistral Reasoning Region:us Safetensors Sharded Smiles Tensorflow

Model Card on HF 🤗: https://huggingface.co/futurehouse/ether0

Ether0 Parameters and Internals

LLM Name	Ether0
Repository 🤗	https://huggingface.co/futurehouse/ether0
Base Model(s)	...istral Small 24B Instruct 2501 mistralai/Mistral-Small-24B-Instruct-2501
Model Size	24b
Required VRAM	95.3 GB
Updated	2026-08-07
Maintainer	futurehouse
Model Type	mistral
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-21 4.6 GB: 2-of-21 4.5 GB: 3-of-21 4.5 GB: 4-of-21 4.5 GB: 5-of-21 4.5 GB: 6-of-21 4.5 GB: 7-of-21 4.5 GB: 8-of-21 4.5 GB: 9-of-21 4.5 GB: 10-of-21 4.5 GB: 11-of-21 4.5 GB: 12-of-21 4.5 GB: 13-of-21 4.5 GB: 14-of-21 4.5 GB: 15-of-21 4.5 GB: 16-of-21 4.5 GB: 17-of-21 4.5 GB: 18-of-21 4.5 GB: 19-of-21 4.5 GB: 20-of-21 4.7 GB: 21-of-21
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	LlamaTokenizerFast
Vocabulary Size	131136
Torch Data Type	float32

Rank the Ether0 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 Ether0

Best Alternatives	Context / RAM	Downloads	Likes
...ral Nemo Instruct 24B Merge V1	1000K / 24.6 GB	9	0
...all 3.1 24B Instruct 2503 Text	128K / 47.3 GB	12	0
Cydonia 24B V4.3	128K / 47.3 GB	3652	138
Slimaki 24B V1.2	128K / 47.3 GB	28	6
Neural V1 24B	128K / 47.3 GB	9	3
MS3.2 PaintedFantasy V4.1 24B	128K / 47.3 GB	80	18
Cydonia 24B V4.1	128K / 47.3 GB	2162	80
Slimaki 24B V1	128K / 47.3 GB	15	10
Asmodeus 24B V1	128K / 47.3 GB	83	13
MS3.2 PaintedFantasy V3 24B	128K / 47.3 GB	28	35

Note: green Score (e.g. "73.2") means that the model is better than futurehouse/ether0.