What are the hardware requirements for Oblivionsend?

Oblivionsend requires approximately 18.6 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 Oblivionsend and how large is it?

Oblivionsend is developed by mehmetkeremturkcan, a model with 9b 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 Oblivionsend?

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

Oblivionsend by mehmetkeremturkcan — VRAM 18.6GB, 8K context

Name: Oblivionsend
Author: mehmetkeremturkcan

Oblivionsend is an open-source language model by mehmetkeremturkcan. Features: 9b LLM, VRAM: 18.6GB, Context: 8K, License: gemma, LLM Explorer Score: 0.16.

Base model:finetune:google/gem... Base model:google/gemma-2-9b-i... Conversational Creative-writing Dataset:sam-paech/gutenberg3-g... Dataset:sam-paech/gutenbergs 1... En Endpoints compatible Gemma2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mehmetkeremturkcan/oblivionsend

Oblivionsend Parameters and Internals

LLM Name	Oblivionsend
Repository 🤗	https://huggingface.co/mehmetkeremturkcan/oblivionsend
Base Model(s)	Gemma 2 9B It google/gemma-2-9b-it
Model Size	9b
Required VRAM	18.6 GB
Updated	2026-08-03
Maintainer	mehmetkeremturkcan
Model Type	gemma2
Model Files	4.9 GB: 1-of-4 5.0 GB: 2-of-4 5.0 GB: 3-of-4 3.7 GB: 4-of-4
Supported Languages	en
Model Architecture	Gemma2ForCausalLM
License	gemma
Context Length	8192
Model Max Length	8192
Transformers Version	4.46.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Oblivionsend 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 Oblivionsend

Best Alternatives	Context / RAM	Downloads	Likes
G2 GSHT 32K	32K / 20.4 GB	8	1
SystemGemma2 9B It	32K / 18.6 GB	5	2
Gemma 2 9B It	8K / 18.6 GB	80757	11
GWQ 9B Preview2	8K / 18.6 GB	11	10
Gemma 2 9B It	8K / 18.6 GB	6	0
Gemma 2 9B It SimPO	8K / 18.6 GB	473	173
Gemma 2 9B It	8K / 18.6 GB	323635	837
Gemma 2 9B It Blend Rebase	8K / 20.4 GB	5	0
Gemma 2 9B JEE Socratic Final	8K / 18.6 GB	1118	0
Gemma 2 9B	8K / 37.1 GB	95888	717

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