What are the hardware requirements for Rombo LLM V2.7 Mist Nemo 12B?

Rombo LLM V2.7 Mist Nemo 12B requires approximately 24.5 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 Rombo LLM V2.7 Mist Nemo 12B and how large is it?

Rombo LLM V2.7 Mist Nemo 12B is developed by Rombo-Org, a model with 12b 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 Rombo LLM V2.7 Mist Nemo 12B?

Rombo LLM V2.7 Mist Nemo 12B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Rombo LLM V2.7 Mist Nemo 12B by Rombo-Org — VRAM 24.5GB, 1000K context

Name: Rombo LLM V2.7 Mist Nemo 12B
Author: Rombo-Org

Rombo LLM V2.7 Mist Nemo 12B is an open-source language model by Rombo-Org. Features: 12b LLM, VRAM: 24.5GB, Context: 1000K, License: apache-2.0, Instruction-Based, Merged, LLM Explorer Score: 0.16.

Merged Model Base model:finetune:mistralai/... Base model:mistralai/mistral-n... Endpoints compatible Instruct Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Rombo-Org/Rombo-LLM-V2.7-mist-nemo-12b

Rombo LLM V2.7 Mist Nemo 12B Parameters and Internals

LLM Name	Rombo LLM V2.7 Mist Nemo 12B
Repository 🤗	https://huggingface.co/Rombo-Org/Rombo-LLM-V2.7-mist-nemo-12b
Base Model(s)	Mistral Nemo Instruct 2407 mistralai/Mistral-Nemo-Instruct-2407
Merged Model	Yes
Model Size	12b
Required VRAM	24.5 GB
Updated	2026-07-19
Maintainer	Rombo-Org
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
License	apache-2.0
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.48.0.dev0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Rombo LLM V2.7 Mist Nemo 12B 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 Rombo LLM V2.7 Mist Nemo 12B

Best Alternatives	Context / RAM	Downloads	Likes
...r Nemo 12B Instruct R 21 09 24	1000K / 24.5 GB	396277	141
Qliphoth 12B V1.1	1000K / 24.5 GB	22	3
Qliphoth 12B V1	1000K / 24.5 GB	26	2
SauerkrautLM Nemo 12B Instruct	1000K / 24.5 GB	1473	22
Magnum V4 12B	1000K / 24.5 GB	1116	54
MN Slush	1000K / 24.5 GB	181	32
...g M Claude Opus High Reasoning	1000K / 24.5 GB	82	3
ChatWaifu V1.4	1000K / 24.5 GB	335	20
ChatWaifu 12B V2.0	1000K / 24.5 GB	175	22
Mistral Nemo Bophades 12B	1000K / 24.5 GB	18	9

Note: green Score (e.g. "73.2") means that the model is better than Rombo-Org/Rombo-LLM-V2.7-mist-nemo-12b.