What are the hardware requirements for DECYPHERS PRIME 2.0?

DECYPHERS PRIME 2.0 requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed DECYPHERS PRIME 2.0 and how large is it?

DECYPHERS PRIME 2.0 is developed by Klevin, 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 DECYPHERS PRIME 2.0?

DECYPHERS PRIME 2.0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

DECYPHERS PRIME 2.0 by Klevin — VRAM 0.2GB

Name: DECYPHERS PRIME 2.0
Author: Klevin

DECYPHERS PRIME 2.0 is an open-source language model by Klevin. Features: 8b LLM, VRAM: 0.2GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

4bit Base model:finetune:unsloth/ll... Base model:unsloth/llama-3-8b-... En Endpoints compatible Instruct Llama Lora Quantized Region:us Safetensors Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/Klevin/DECYPHERS-PRIME-2.0

DECYPHERS PRIME 2.0 Parameters and Internals

Model Type

text-generation-inference, transformers

Training Details

Methodology:

Trained 2x faster using Unsloth and Huggingface's TRL library

LLM Name	DECYPHERS PRIME 2.0
Repository 🤗	https://huggingface.co/Klevin/DECYPHERS-PRIME-2.0
Base Model(s)	Llama 3 8B Instruct Bnb 4bit unsloth/llama-3-8b-Instruct-bnb-4bit
Model Size	8b
Required VRAM	0.2 GB
Updated	2026-08-05
Maintainer	Klevin
Instruction-Based	Yes
Model Files	0.2 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	AutoModel
License	apache-2.0
Is Biased	none
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	v_proj\|down_proj\|q_proj\|gate_proj\|up_proj\|o_proj\|k_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the DECYPHERS PRIME 2.0 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 DECYPHERS PRIME 2.0

Best Alternatives	Context / RAM	Downloads	Likes
My Custom Llm	0K / 0.2 GB	18	1
Novashop Support Lora	0K / 0.2 GB	9	1
Torki Lora	0K / 0 GB	5	0
...a 3 8B Bnb 4bit Robot Instruct	0K / 0.2 GB	8	0
Llama 3 Instruct LiPPA LoRA 8B	0K / 2.7 GB	6	0
...lama 3 LimaRP Instruct LoRA 8B	0K / 2.7 GB	5	0
...uct Bnb Lora MedicalQnADataset	0K / 0.3 GB	0	1
Nextjs App V0.1	0K / 0.2 GB	0	2
Training Test 921 1	0K / 1.3 GB	24	0
Ur Orpo Adapter	0K / 0.2 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than Klevin/DECYPHERS-PRIME-2.0.