What are the hardware requirements for Qwen3.8 0.8B Agentic Distill?

Qwen3.8 0.8B Agentic Distill requires approximately 1.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 0.8B Agentic Distill and how large is it?

Qwen3.8 0.8B Agentic Distill is developed by gatilin, 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 Qwen3.8 0.8B Agentic Distill?

Qwen3.8 0.8B Agentic Distill is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 0.8B Agentic Distill by gatilin — VRAM 1.7GB

Name: Qwen3.8 0.8B Agentic Distill
Author: gatilin

Qwen3.8 0.8B Agentic Distill is an open-source language model by gatilin. Features: 0.8b LLM, VRAM: 1.7GB, License: mit, LLM Explorer Score: 0.27.

Qwen3 5 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/gatilin/Qwen3.8-0.8B-Agentic-distill

Qwen3.8 0.8B Agentic Distill Parameters and Internals

LLM Name	Qwen3.8 0.8B Agentic Distill
Repository 🤗	https://huggingface.co/gatilin/Qwen3.8-0.8B-Agentic-distill
Model Size	0.8b
Required VRAM	1.7 GB
Updated	2026-08-31
Maintainer	gatilin
Model Type	qwen3_5
Model Files	1.7 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	mit
Model Max Length	262144
Transformers Version	5.8.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 0.8B Agentic Distill 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 Qwen3.8 0.8B Agentic Distill

Best Alternatives	Context / RAM	Downloads	Likes
OvisOCR2	0K / 1.7 GB	145589	449
Qwen3.5 0.8B	0K / 1.8 GB	2839884	655
Qwen3.5 0.8B Base	0K / 1.8 GB	828054	92
Qwen3.5 0.8B	0K / 1.8 GB	47663	19
Soreqen S1 Mini	0K / 1.7 GB	288	1
AfriqueQwen3.5 0.8B 50Langs	0K / 2.2 GB	364	2
SingGuard NSFA 0.8B	0K / 2.2 GB	953	5
Ai Course Classifier	0K / 1.7 GB	161	1
Qwen3.5 0.8B Manumit V1	0K / 1.7 GB	129	0
Qwen3.5 0.8B Base	0K / 1.7 GB	4439	3

Note: green Score (e.g. "73.2") means that the model is better than gatilin/Qwen3.8-0.8B-Agentic-distill.