What are the hardware requirements for Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled?

Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled requires approximately 55.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled and how large is it?

Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled is developed by TheCyberVine, 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 27B Claude 4.6 Opus Reasoning Distilled?

Qwen3.5 27B 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 27B Claude 4.6 Opus Reasoning Distilled by TheCyberVine — VRAM 55.2GB

Name: Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled
Author: TheCyberVine

Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled is an open-source language model by TheCyberVine. Features: 27b LLM, VRAM: 55.2GB, License: apache-2.0, LLM Explorer Score: 0.23.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-27b Chain-of-thought Conversational Dataset:jackrong/qwen3.5-reaso... Dataset:nohurry/opus-4.6-reaso... Dense En Qwen Qwen3.5 Qwen3 5 Reasoning Region:us Safetensors Sharded Tensorflow Unsloth Zh

Model Card on HF 🤗: https://huggingface.co/TheCyberVine/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled

Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled Parameters and Internals

LLM Name	Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled
Repository 🤗	https://huggingface.co/TheCyberVine/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled
Model Name	qwen/Qwen3.5-27B
Base Model(s)	Qwen/Qwen3.5-27B Qwen/Qwen3.5-27B
Model Size	27b
Required VRAM	55.2 GB
Updated	2026-08-08
Maintainer	TheCyberVine
Model Type	qwen3_5
Model Files	5.3 GB: 1-of-11 5.3 GB: 2-of-11 5.3 GB: 3-of-11 5.3 GB: 4-of-11 5.3 GB: 5-of-11 5.3 GB: 6-of-11 5.3 GB: 7-of-11 5.4 GB: 8-of-11 5.3 GB: 9-of-11 5.3 GB: 10-of-11 2.1 GB: 11-of-11
Supported Languages	en zh
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled capabilities

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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 27B Claude 4.6 Opus Reasoning Distilled

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
Qwen3.8 27B Escha W2	0K / 10.1 GB	561	97
ThinkingCap Qwen3.6 27B	0K / 54.7 GB	35947	614
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342
Qwen3.5 27B	0K / 55.2 GB	2536294	1028
Qwen3.5 27B	0K / 55.2 GB	8115	16

Note: green Score (e.g. "73.2") means that the model is better than TheCyberVine/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled.