What are the hardware requirements for ThinkingCap Qwen3.6 27B NVFP4?

ThinkingCap Qwen3.6 27B NVFP4 requires approximately 19.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed ThinkingCap Qwen3.6 27B NVFP4 and how large is it?

ThinkingCap Qwen3.6 27B NVFP4 is developed by bottlecapai, 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 ThinkingCap Qwen3.6 27B NVFP4?

ThinkingCap Qwen3.6 27B NVFP4 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ThinkingCap Qwen3.6 27B NVFP4 by bottlecapai — VRAM 19.8GB

Name: ThinkingCap Qwen3.6 27B NVFP4
Author: bottlecapai

ThinkingCap Qwen3.6 27B NVFP4 is an open-source language model by bottlecapai. Features: 27b LLM, VRAM: 19.8GB, License: apache-2.0, LLM Explorer Score: 0.34.

8-bit Base model:bottlecapai/thinkin... Base model:quantized:bottlecap... Compressed-tensors Conversational Efficient-thinking Endpoints compatible Fp4 Image-text-to-text Nvfp4 Qwen3 5 Qwen3 6 Region:us Safetensors Sharded Tensorflow Token-efficient Vllm

Model Card on HF 🤗: https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.6-27B-NVFP4

ThinkingCap Qwen3.6 27B NVFP4 Parameters and Internals

LLM Name	ThinkingCap Qwen3.6 27B NVFP4
Repository 🤗	https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.6-27B-NVFP4
Base Model(s)	bottlecapai/ThinkingCap-Qwen3.6-27B bottlecapai/ThinkingCap-Qwen3.6-27B
Model Size	27b
Required VRAM	19.8 GB
Updated	2026-08-11
Maintainer	bottlecapai
Model Type	qwen3_5
Model Files	10.0 GB: 1-of-2 9.8 GB: 2-of-2 0.8 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.10.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the ThinkingCap Qwen3.6 27B NVFP4 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 ThinkingCap Qwen3.6 27B NVFP4

Best Alternatives	Context / RAM	Downloads	Likes
...wopus3.8 27B Flash Mlx OQ4e 1M	1024K / 16.9 GB	211	1
Agens Pilot	1024K / 54.7 GB	87	3
Qwen3.8 27B NPU2	256K / GB	252	4
JEV 27B VL	0K / 55.6 GB	1525286	966
Clef	0K / 54.7 GB	9513	1835
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416

Note: green Score (e.g. "73.2") means that the model is better than bottlecapai/ThinkingCap-Qwen3.6-27B-NVFP4.