What are the hardware requirements for Nemo Instruct Books Model Stock?

Nemo Instruct Books Model Stock requires approximately 24.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nemo Instruct Books Model Stock and how large is it?

Nemo Instruct Books Model Stock is developed by Burnt-Toast, a model with 12.2b 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 Nemo Instruct Books Model Stock?

Nemo Instruct Books Model Stock is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nemo Instruct Books Model Stock by Burnt-Toast — VRAM 24.5GB, 128K context

Name: Nemo Instruct Books Model Stock
Author: Burnt-Toast

Nemo Instruct Books Model Stock is an open-source language model by Burnt-Toast. Features: 12.2b LLM, VRAM: 24.5GB, Context: 128K, Instruction-Based, Merged, LLM Explorer Score: 0.19.

Merged Model Arxiv:2403.19522 Base model:mistralai/mistral-n... Base model:toastypigeon/nemo-b... Base model:toastypigeon/nemo-b... Base model:toastypigeon/nemo-b... Base model:toastypigeon/nemo-b... Conversational Endpoints compatible Instruct Lora Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Burnt-Toast/nemo-instruct-books-model-stock

Nemo Instruct Books Model Stock Parameters and Internals

LLM Name	Nemo Instruct Books Model Stock
Repository 🤗	https://huggingface.co/Burnt-Toast/nemo-instruct-books-model-stock
Base Model(s)	Mistral Nemo Instruct 2407 ToastyPigeon/nemo-books-lora-3 Mistral Nemo Instruct 2407 ToastyPigeon/nemo-books-lora-2 Mistral Nemo Instruct 2407 Nemo Books Lora 4 Mistral Nemo Instruct 2407 Nemo Books Lora Mistral Nemo Instruct 2407 mistralai/Mistral-Nemo-Instruct-2407 ToastyPigeon/nemo-books-lora-3 mistralai/Mistral-Nemo-Instruct-2407 ToastyPigeon/nemo-books-lora-2 mistralai/Mistral-Nemo-Instruct-2407 ToastyPigeon/nemo-books-lora-4 mistralai/Mistral-Nemo-Instruct-2407 ToastyPigeon/nemo-books-lora mistralai/Mistral-Nemo-Instruct-2407
Merged Model	Yes
Model Size	12.2b
Required VRAM	24.5 GB
Updated	2026-08-20
Maintainer	Burnt-Toast
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 4.9 GB: 5-of-5
Model Architecture	MistralForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.53.1
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072
LoRA Model	Yes
Torch Data Type	bfloat16

Rank the Nemo Instruct Books Model Stock 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 Nemo Instruct Books Model Stock

Best Alternatives	Context / RAM	Downloads	Likes
...istral Nemo Instruct 2407 MPOA	1000K / 24.5 GB	37	3
...ish Mistral Nemo Instruct 2407	1000K / 24.5 GB	77	2
Mistral Nemo Kurdish	1000K / 24.5 GB	37	3
Violet Twilight V0.2	1000K / 24.5 GB	66	49
Kalypso	1000K / 24.5 GB	45	24
Crimson Dawn V0.2	1000K / 24.5 GB	17	13
Azure Dusk V0.2	1000K / 24.5 GB	43	10
...al Nemo Japanese Instruct 2408	1000K / 24.5 GB	2358	49
Mistral Nemo Instruct 2407 FP8	1000K / 13.6 GB	4691	19
Educa Ai Nemo Sft	1000K / 49.3 GB	13	4

Note: green Score (e.g. "73.2") means that the model is better than Burnt-Toast/nemo-instruct-books-model-stock.