What are the hardware requirements for Nail Qwen3.6 35B A3B MLX 5bit?

Nail Qwen3.6 35B A3B MLX 5bit requires approximately 27.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nail Qwen3.6 35B A3B MLX 5bit and how large is it?

Nail Qwen3.6 35B A3B MLX 5bit is developed by peculiar-ragdoll, 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 Nail Qwen3.6 35B A3B MLX 5bit perform on standard benchmarks?

Nail Qwen3.6 35B A3B MLX 5bit has the following published scores: LMSYS ELO 1395. Compare against reference models on this page or on the LLM Explorer leaderboards.

Nail Qwen3.6 35B A3B MLX 5bit by peculiar-ragdoll — VRAM 27.5GB

Name: Nail Qwen3.6 35B A3B MLX 5bit
Author: peculiar-ragdoll

Nail Qwen3.6 35B A3B MLX 5bit is an open-source language model by peculiar-ragdoll. Features: 35b LLM, VRAM: 27.5GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.44, ELO: 1395.

5-bit 5bit 8-bit Agentic-coding Base model:quantized:qwen/qwen... Base model:qwen/qwen3.6-35b-a3... Conversational Efficient-thinking En Image-text-to-text Mlx Moe Quantized Qwen3 5 moe Qwen3 6 Region:us Safetensors Sharded Tensorflow Token-efficient Zh

Model Card on HF 🤗: https://huggingface.co/peculiar-ragdoll/Nail-Qwen3.6-35B-A3B-MLX-5bit

Nail Qwen3.6 35B A3B MLX 5bit 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)

Nail Qwen3.6 35B A3B MLX 5bit Parameters and Internals

LLM Name	Nail Qwen3.6 35B A3B MLX 5bit
Repository 🤗	https://huggingface.co/peculiar-ragdoll/Nail-Qwen3.6-35B-A3B-MLX-5bit
Base Model(s)	Qwen/Qwen3.6-35B-A3B Qwen/Qwen3.6-35B-A3B
Model Size	35b
Required VRAM	27.5 GB
Updated	2026-08-19
Maintainer	peculiar-ragdoll
Model Type	qwen3_5_moe
Model Files	5.4 GB: 1-of-6 5.4 GB: 2-of-6 5.3 GB: 3-of-6 5.4 GB: 4-of-6 5.2 GB: 5-of-6 0.8 GB: 6-of-6 1.7 GB
Supported Languages	en zh
Quantization Type	5bit
Model Architecture	Qwen3_5MoeForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	4.57.6
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Errors	replace

Rank the Nail Qwen3.6 35B A3B MLX 5bit 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 Nail Qwen3.6 35B A3B MLX 5bit

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.6 35B A3B MLX 4bit	0K / 20.5 GB	513193	6
Qwen3.6 35B A3B MLX 6bit	0K / 28.9 GB	478592	2
Qwen3.6 35B A3B MLX 8bit	0K / 37.8 GB	473537	1
Qwen3.6 35B A3B UD MLX 4bit	0K / 21.6 GB	15720	112
Qwen3.6 35B A3B MLX 8bit	0K / 37.8 GB	3862	41
Qwen3.6 35B A3B 6bit	0K / 28.9 GB	2742	8
Qwen3.6 35B A3B UD MLX 3bit	0K / 17.3 GB	2292	13
Qwen3.6 35B A3B 5bit	0K / 24.7 GB	1628	5
Qwen3.6 35B A3B 4bit	0K / 20.5 GB	62036	92
Qwen3.6 35B A3B 8bit	0K / 37.8 GB	120175	27

Note: green Score (e.g. "73.2") means that the model is better than peculiar-ragdoll/Nail-Qwen3.6-35B-A3B-MLX-5bit.