What are the hardware requirements for Qwen3.5 35B A3B GGUF?

Qwen3.5 35B A3B GGUF requires approximately 0.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 35B A3B GGUF and how large is it?

Qwen3.5 35B A3B GGUF is developed by unsloth, a model with 35b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Qwen3.5 35B A3B GGUF perform on standard benchmarks?

Qwen3.5 35B A3B GGUF has the following published scores: LMSYS ELO 1395. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen3.5 35B A3B GGUF by unsloth — VRAM 0.9GB

Name: Qwen3.5 35B A3B GGUF
Author: unsloth

Qwen3.5 35B A3B GGUF is an open-source language model by unsloth. Features: 35b LLM, VRAM: 0.9GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.53, ELO: 1395.

Base model:quantized:qwen/qwen... Base model:qwen/qwen3.5-35b-a3... Conversational Endpoints compatible Gguf Image-text-to-text Imatrix Q3 Quantized Qwen3 5 moe Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen3.5-35B-A3B-GGUF

Qwen3.5 35B A3B GGUF Benchmarks

LMSys ELO 1395 vs 1272 (so35) 9.7%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen3.5 35B A3B GGUF Parameters and Internals

LLM Name	Qwen3.5 35B A3B GGUF
Repository 🤗	https://huggingface.co/unsloth/Qwen3.5-35B-A3B-GGUF
Base Model(s)	Qwen/Qwen3.5-35B-A3B Qwen/Qwen3.5-35B-A3B
Model Size	35b
Required VRAM	0.9 GB
Updated	2026-08-10
Maintainer	unsloth
Model Type	qwen3_5_moe
Model Files	21.6 GB 16.4 GB 15.3 GB 22.0 GB 20.7 GB 26.2 GB 24.8 GB 28.9 GB 36.9 GB 11.4 GB 10.7 GB 13.6 GB 13.1 GB 17.8 GB 17.5 GB 12.2 GB 16.6 GB 20.2 GB 22.2 GB 26.4 GB 28.5 GB 32.1 GB 48.7 GB 0.9 GB 0.9 GB 1.8 GB
GGUF Quantization	Yes
Quantization Type	gguf\|q3\|q4_k\|q5_k
Model Architecture	Qwen3_5MoeForConditionalGeneration
License	apache-2.0
Transformers Version	5.3.0.dev0

Rank the Qwen3.5 35B A3B GGUF 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

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