What are the hardware requirements for GEMMA2 27B NLI 16bit?

GEMMA2 27B NLI 16bit requires approximately 54.7 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GEMMA2 27B NLI 16bit and how large is it?

GEMMA2 27B NLI 16bit is developed by 1024m, a model with 27b 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 GEMMA2 27B NLI 16bit?

GEMMA2 27B NLI 16bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GEMMA2 27B NLI 16bit by 1024m — VRAM 54.7GB, 8K context

Name: GEMMA2 27B NLI 16bit
Author: 1024m

GEMMA2 27B NLI 16bit is an open-source language model by 1024m. Features: 27b LLM, VRAM: 54.7GB, Context: 8K, License: apache-2.0, Quantized, LLM Explorer Score: 0.14.

4bit Base model:finetune:unsloth/ge... Base model:unsloth/gemma-2-27b... En Endpoints compatible Gemma2 Quantized Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/1024m/GEMMA2-27B-NLI-16bit

GEMMA2 27B NLI 16bit Parameters and Internals

Model Type

text-generation-inference, transformers, trl, sft

Additional Notes

This gemma2 model was trained 2x faster with Unsloth and Huggingface's TRL library.

Supported Languages

en ()

Training Details

Methodology:

Finetuned from model : unsloth/gemma-2-27b-bnb-4bit using Unsloth and Huggingface's TRL library

LLM Name	GEMMA2 27B NLI 16bit
Repository 🤗	https://huggingface.co/1024m/GEMMA2-27B-NLI-16bit
Base Model(s)	Gemma 2 27B Bnb 4bit unsloth/gemma-2-27b-bnb-4bit
Model Size	27b
Required VRAM	54.7 GB
Updated	2026-09-12
Maintainer	1024m
Model Type	gemma2
Model Files	4.7 GB: 1-of-12 4.9 GB: 2-of-12 4.9 GB: 3-of-12 5.0 GB: 4-of-12 4.9 GB: 5-of-12 4.9 GB: 6-of-12 5.0 GB: 7-of-12 4.9 GB: 8-of-12 4.9 GB: 9-of-12 5.0 GB: 10-of-12 4.9 GB: 11-of-12 0.7 GB: 12-of-12
Supported Languages	en
Quantization Type	4bit
Model Architecture	Gemma2ForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.44.0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the GEMMA2 27B NLI 16bit 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 GEMMA2 27B NLI 16bit

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 2 27B 8bit	8K / 28.8 GB	11	2
Gemma 2 27B 4bit	8K / 15.3 GB	9	0
Gemma2 Mixed Therapy Ft	8K / 15.8 GB	5	2
Gemma 2 27B It Bnb 4bit	8K / 15.8 GB	830	11
Gemma 2 27B It 4bit	8K / 15.3 GB	372	8
Gemma 2 27B It 8bit	8K / 28.8 GB	152	10
Gemma 2 27B Bnb 4bit	8K / 15.8 GB	90	13
Gemma 2 27B It 4bit	8K / 15.8 GB	20	3
ATOMIS	32K / 66 GB	7	8
SystemGemma2 27B It	32K / 54.7 GB	96	1

Note: green Score (e.g. "73.2") means that the model is better than 1024m/GEMMA2-27B-NLI-16bit.