What are the hardware requirements for Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled?

Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled requires approximately 9.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled and how large is it?

Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled is developed by Jackrong, a model with 4b 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 4B Claude 4.6 Opus Reasoning Distilled?

Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled by Jackrong — VRAM 9.3GB

Name: Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled
Author: Jackrong

Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled is an open-source language model by Jackrong. Features: 4b LLM, VRAM: 9.3GB, License: apache-2.0, LLM Explorer Score: 0.25.

Base model:adapter:qwen/qwen3.... Base model:qwen/qwen3.5-4b Chain-of-thought Conversational Dataset:jackrong/qwen3.5-reaso... Dataset:nohurry/opus-4.6-reaso... En Image-text-to-text Ko Lora Qwen Qwen3.5 Qwen3 5 Reasoning Region:us Safetensors Sharded Tensorflow Unsloth Zh

Model Card on HF 🤗: https://huggingface.co/Jackrong/Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled

Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled Parameters and Internals

LLM Name	Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled
Repository 🤗	https://huggingface.co/Jackrong/Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled
Model Name	unsloth/Qwen3.5-4B
Base Model(s)	Qwen/Qwen3.5-4B Qwen/Qwen3.5-4B
Model Size	4b
Required VRAM	9.3 GB
Updated	2026-07-29
Maintainer	Jackrong
Model Type	qwen3_5
Model Files	5.3 GB: 1-of-2 4.0 GB: 2-of-2
Supported Languages	en zh ko
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Tokenizer Class	TokenizersBackend
Padding Token	<\|vision_pad\|>
LoRA Model	Yes
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled 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

Quantized Models of the Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled

Model	Likes	Downloads	VRAM
...aude 4.6 Opus Abliterated 4bit	5	516	3 GB
...aude 4.6 Opus Abliterated 6bit	3	188	4 GB

Best Alternatives to Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.5 4B	0K / 9.3 GB	6575502	801
NuExtract3	0K / 0.2 GB	441570	324
Agents A1 4B	0K / 9.1 GB	177578	72
CogEvol 4B	0K / 9.1 GB	582	25
Qwen3.8 4B Distill	0K / 9.3 GB	1878	26
Qwen3.5 4B Base	0K / 9.3 GB	227814	79
Fara1.5 4B	0K / 9.1 GB	4934	39
Qwen3.5 4B	0K / 9.3 GB	139961	26
Qwen35 4b Sft VE	0K / 9.1 GB	3663	0
DeepSeek V4 Pro Qwen3.5 4B	0K / 9.3 GB	3476	9

Note: green Score (e.g. "73.2") means that the model is better than Jackrong/Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled.