What are the hardware requirements for Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm?

Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm requires approximately 23 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm and how large is it?

Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm is developed by rdtand, a model with 35b 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 Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm?

Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm by rdtand — VRAM 23GB

Name: Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm
Author: rdtand

Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm is an open-source language model by rdtand. Features: 35b LLM, VRAM: 23GB, License: apache-2.0, LLM Explorer Score: 0.33.

8-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen3.6-35b-a3... Compressed-tensors Conversational Deltanet En Image-text-to-text Mixed-precision Moe Mtp Multilingual Multimodal Mxfp8 Nvfp4 Prismaquant Quantized Qwen3.6 Qwen3 5 moe Region:us Safetensors Sharded Speculative-decoding Tensorflow Vision Vision-language Vllm

Model Card on HF 🤗: https://huggingface.co/rdtand/Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm

Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm Parameters and Internals

LLM Name	Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm
Repository 🤗	https://huggingface.co/rdtand/Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm
Base Model(s)	Qwen/Qwen3.6-35B-A3B Qwen/Qwen3.6-35B-A3B
Model Size	35b
Required VRAM	23 GB
Updated	2026-07-14
Maintainer	rdtand
Model Type	qwen3_5_moe
Model Files	4.6 GB: 1-of-6 4.6 GB: 2-of-6 4.6 GB: 3-of-6 4.6 GB: 4-of-6 4.6 GB: 5-of-6 0.0 GB: 6-of-6
Supported Languages	en
Model Architecture	Qwen3_5MoeForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	4.57.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm 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 Qwen3.6 35B A3B PrismaQuant 4.75bit Vllm

Best Alternatives	Context / RAM	Downloads	Likes
Ornith 1.5 35B A3B NPU2	256K / GB	145	1
Qwen3.6 35B A3B	0K / 72.2 GB	5540855	2648
Qwen3.5 35B A3B	0K / 72.3 GB	2158511	1482
Ornith 1.0 35B	0K / 70.4 GB	3056578	504
Qwen3.6 35B A3B NVFP4	0K / 23.4 GB	8788684	482
KAT Coder V2.5 Dev	0K / 69.7 GB	17885	537
Qwen3.6 35B A3B FP8	0K / 0.8 GB	8984811	343
Qwen AgentWorld 35B A3B	0K / 69.2 GB	66155	665
Ornith 1.5 35B A3B	0K / 72.1 GB	1713	201
Qwen3.6 35B A3B NVFP4 Fast	0K / 23.6 GB	463661	98

Note: green Score (e.g. "73.2") means that the model is better than rdtand/Qwen3.6-35B-A3B-PrismaQuant-4.75bit-vllm.