What are the hardware requirements for Delentia Slm Jitna V0.4?

Delentia Slm Jitna V0.4 requires approximately 16.1 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 Delentia Slm Jitna V0.4 and how large is it?

Delentia Slm Jitna V0.4 is developed by Delentia, a model with 8b 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 Delentia Slm Jitna V0.4?

Delentia Slm Jitna V0.4 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Delentia Slm Jitna V0.4 by Delentia — VRAM 16.1GB, 128K context

Name: Delentia Slm Jitna V0.4
Author: Delentia

Delentia Slm Jitna V0.4 is an open-source language model by Delentia. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, License: apache-2.0, Quantized, LLM Explorer Score: 0.27.

Base model:meta-llama/llama-3.... Base model:quantized:meta-llam... Constitutional-ai Conversational Delentia-os En Endpoints compatible Gguf Jitna Llama Llama-3 Llama-3.1 Multi-adapter Peer-reviewed Q4 Qlora Quantized Region:us Safetensors Sharded Tensorflow Th Thai Unsloth Whitepaper Zenodo

Model Card on HF 🤗: https://huggingface.co/Delentia/delentia-slm-jitna-v0.4

Delentia Slm Jitna V0.4 Parameters and Internals

LLM Name	Delentia Slm Jitna V0.4
Repository 🤗	https://huggingface.co/Delentia/delentia-slm-jitna-v0.4
Base Model(s)	meta-llama/Meta-Llama-3.1-8B meta-llama/Meta-Llama-3.1-8B
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-08-14
Maintainer	Delentia
Model Type	llama
Model Files	4.9 GB 4.9 GB 4.9 GB 5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Supported Languages	en th
GGUF Quantization	Yes
Quantization Type	q4\|gguf\|q4_k
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Tokenizer Class	TokenizersBackend
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Delentia Slm Jitna V0.4 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 Delentia Slm Jitna V0.4

Best Alternatives	Context / RAM	Downloads	Likes
10K V6	1024K / 16.1 GB	5	0
...truct Gradient 1048K IMat GGUF	1024K / 2 GB	650	6
...B Instruct Gradient 1048K GGUF	1024K / 3.2 GB	445	3
Unhinged Llama3 8B 524K	512K / 26.5 GB	25	0
Llama 3 8B Instruct 262K GGUF	256K / 3.2 GB	208	2
Dolphin3 Cyber 8B GGUF	128K / 3.2 GB	59950	150
Grok Oss Apollyon 8B	128K / 16.1 GB	3449	8
Grok Oss Revenant 8B	128K / 16.1 GB	324	0
...pSeek R1 Distill Llama 8B GGUF	128K / 2.2 GB	32729	306
Llama 3.1 8B Instruct GGUF	128K / 2.2 GB	17956	41

Note: green Score (e.g. "73.2") means that the model is better than Delentia/delentia-slm-jitna-v0.4.