What are the hardware requirements for Jpt 0.8B?

Jpt 0.8B requires approximately 1.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Jpt 0.8B and how large is it?

Jpt 0.8B is developed by kirp, a model with 0.8b 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 Jpt 0.8B?

Jpt 0.8B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Jpt 0.8B by kirp — VRAM 1.7GB

Name: Jpt 0.8B
Author: kirp

Jpt 0.8B is an open-source language model by kirp. Features: 0.8b LLM, VRAM: 1.7GB, License: cc-by-nc-4.0, LLM Explorer Score: 0.28.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-0.8b Calibration Classification Conversational Decision-model Endpoints compatible Image-text-to-text Multimodal Qwen3 5 Region:us Safetensors Typed-decisions

Model Card on HF 🤗: https://huggingface.co/kirp/jpt-0.8b

Jpt 0.8B Parameters and Internals

LLM Name	Jpt 0.8B
Repository 🤗	https://huggingface.co/kirp/jpt-0.8b
Base Model(s)	Qwen/Qwen3.5-0.8B Qwen/Qwen3.5-0.8B
Model Size	0.8b
Required VRAM	1.7 GB
Updated	2026-09-30
Maintainer	kirp
Model Type	qwen3_5
Model Files	1.7 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	cc-by-nc-4.0
Model Max Length	262144
Transformers Version	5.16.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Jpt 0.8B 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 Jpt 0.8B

Best Alternatives	Context / RAM	Downloads	Likes
OvisOCR2	0K / 1.7 GB	251327	486
LightOnOCR 3 0.8B	0K / 1.7 GB	1318	48
Qwen3.5 0.8B	0K / 1.8 GB	2839884	655
Qwen3.5 0.8B Base	0K / 1.8 GB	828054	92
Xiaomi OCR 0	0K / 1.8 GB	933	15
Tev1 0.8B Onnx Webgpu	0K / GB	1336	1
Tev1 0.8B Experimental	0K / 1.8 GB	644	9
Intern Decision 0.8B	0K / 0.2 GB	242	16
OneJev 0.8B	0K / 2.2 GB	1101	2
Qwen3.5 0.8B	0K / 1.8 GB	47663	19

Note: green Score (e.g. "73.2") means that the model is better than kirp/jpt-0.8b.