What are the hardware requirements for Fireball Mistral Nemo Instruct 24B Merge V1?

Fireball Mistral Nemo Instruct 24B Merge V1 requires approximately 24.6 GB of VRAM and supports a context window of 1000K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Fireball Mistral Nemo Instruct 24B Merge V1 and how large is it?

Fireball Mistral Nemo Instruct 24B Merge V1 is developed by EpistemeAI, 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 Fireball Mistral Nemo Instruct 24B Merge V1?

Fireball Mistral Nemo Instruct 24B Merge V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Fireball Mistral Nemo Instruct 24B Merge V1 by EpistemeAI — VRAM 24.6GB, 1000K context

Name: Fireball Mistral Nemo Instruct 24B Merge V1
Author: EpistemeAI

Fireball Mistral Nemo Instruct 24B Merge V1 is an open-source language model by EpistemeAI. Features: 24b LLM, VRAM: 24.6GB, Context: 1000K, License: proprietary, Instruction-Based, Merged, LLM Explorer Score: 0.14.

Merged Model Base model:epistemeai2/firebal... Base model:finetune:epistemeai... Epistemeai2/fireball-mistral-n... Instruct Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/EpistemeAI/Fireball-Mistral-Nemo-Instruct-24B-merge-v1

Fireball Mistral Nemo Instruct 24B Merge V1 Parameters and Internals

Model Type

text-generation

Input Output

Accepted Modalities:

text

Output Format:

text

LLM Name	Fireball Mistral Nemo Instruct 24B Merge V1
Repository 🤗	https://huggingface.co/EpistemeAI/Fireball-Mistral-Nemo-Instruct-24B-merge-v1
Base Model(s)	EpistemeAI2/Fireball-Mistral-Nemo-Instruct-emo-PHD EpistemeAI2/Fireball-Mistral-Nemo-Instruct-emo-PHD EpistemeAI2/Fireball-Mistral-Nemo-Instruct-emo-PHD EpistemeAI2/Fireball-Mistral-Nemo-Instruct-emo-PHD
Merged Model	Yes
Model Size	24b
Required VRAM	24.6 GB
Updated	2024-10-06
Maintainer	EpistemeAI
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-5 4.9 GB: 2-of-5 5.0 GB: 3-of-5 4.9 GB: 4-of-5 4.9 GB: 5-of-5
Gated Model	Yes
Model Architecture	MistralForCausalLM
License	proprietary
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.42.4
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Fireball Mistral Nemo Instruct 24B Merge V1 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 Fireball Mistral Nemo Instruct 24B Merge V1

Best Alternatives	Context / RAM	Downloads	Likes
...all 3.1 24B Instruct 2503 Text	128K / 47.3 GB	16	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	50	13
MS3.2 PaintedFantasy V3 24B	128K / 47.3 GB	28	35
Cydonia 24B V4.2.0	128K / 47.3 GB	34	39

Note: green Score (e.g. "73.2") means that the model is better than EpistemeAI/Fireball-Mistral-Nemo-Instruct-24B-merge-v1.