What are the hardware requirements for Qwen3.5 0.8B Japanese SFT V2?

Qwen3.5 0.8B Japanese SFT V2 requires approximately 1.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 0.8B Japanese SFT V2 and how large is it?

Qwen3.5 0.8B Japanese SFT V2 is developed by Takenoko12345678, a model with 27b 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 Qwen3.5 0.8B Japanese SFT V2?

Qwen3.5 0.8B Japanese SFT V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 0.8B Japanese SFT V2 by Takenoko12345678 — VRAM 1.7GB

Name: Qwen3.5 0.8B Japanese SFT V2
Author: Takenoko12345678

Qwen3.5 0.8B Japanese SFT V2 is an open-source language model by Takenoko12345678. Features: 27b LLM, VRAM: 1.7GB, License: apache-2.0, LLM Explorer Score: 0.33.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-0.8b Conversational Dataset:takenoko12345678/japan... Dataset:takenoko12345678/japan... Dataset:wikimedia/wikipedia Distillation Dpo En Endpoints compatible Full-finetune Image-text-to-text Ja Japanese Qwen3 5 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Takenoko12345678/Qwen3.5-0.8B-Japanese-SFT-v2

Qwen3.5 0.8B Japanese SFT V2 Parameters and Internals

LLM Name	Qwen3.5 0.8B Japanese SFT V2
Repository 🤗	https://huggingface.co/Takenoko12345678/Qwen3.5-0.8B-Japanese-SFT-v2
Base Model(s)	Qwen/Qwen3.5-0.8B Qwen/Qwen3.5-0.8B
Model Size	27b
Required VRAM	1.7 GB
Updated	2026-10-09
Maintainer	Takenoko12345678
Model Type	qwen3_5
Model Files	1.7 GB
Supported Languages	ja en
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.17.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.5 0.8B Japanese SFT V2 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 Qwen3.5 0.8B Japanese SFT V2

Best Alternatives	Context / RAM	Downloads	Likes
...wopus3.8 27B Flash Mlx OQ4e 1M	1024K / 16.9 GB	211	1
Agens Pilot	1024K / 54.7 GB	86	3
Qwen3.8 27B NPU2	256K / GB	252	4
JEV 27B VL	0K / 55.6 GB	1525286	966
Clef	0K / 54.7 GB	9513	1835
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416

Note: green Score (e.g. "73.2") means that the model is better than Takenoko12345678/Qwen3.5-0.8B-Japanese-SFT-v2.