What are the hardware requirements for ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix?

ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix requires approximately 30.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix and how large is it?

ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix is developed by angrykirc, 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 Qwen3.8 27B INT8 W8A8 Imatrix?

ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix by angrykirc — VRAM 30.3GB

Name: ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix
Author: angrykirc

ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix is an open-source language model by angrykirc. Features: 27b LLM, VRAM: 30.3GB, License: other, LLM Explorer Score: 0.29.

8-bit Base model:bottlecapai/thinkin... Base model:quantized:bottlecap... Compressed-tensors Conversational En Endpoints compatible Image-text-to-text Imatrix Int8 Multimodal Quantized Qwen3 5 Region:us Ru Safetensors Sharded Speculative-decoding Tensorflow Vlm W8a8

Model Card on HF 🤗: https://huggingface.co/angrykirc/ThinkingCap-Qwen3.8-27B-INT8-W8A8-imatrix

ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix Parameters and Internals

LLM Name	ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix
Repository 🤗	https://huggingface.co/angrykirc/ThinkingCap-Qwen3.8-27B-INT8-W8A8-imatrix
Base Model(s)	bottlecapai/ThinkingCap-Qwen3.8-27B bottlecapai/ThinkingCap-Qwen3.8-27B
Model Size	27b
Required VRAM	30.3 GB
Updated	2026-09-29
Maintainer	angrykirc
Model Type	qwen3_5
Model Files	2.5 GB: 1-of-15 2.0 GB: 2-of-15 2.0 GB: 3-of-15 2.0 GB: 4-of-15 1.9 GB: 5-of-15 2.0 GB: 6-of-15 2.0 GB: 7-of-15 2.0 GB: 8-of-15 2.0 GB: 9-of-15 1.9 GB: 10-of-15 2.0 GB: 11-of-15 2.0 GB: 12-of-15 2.0 GB: 13-of-15 2.5 GB: 14-of-15 1.5 GB: 15-of-15 0.8 GB
Supported Languages	en ru
Model Architecture	Qwen3_5ForConditionalGeneration
License	other
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the ThinkingCap Qwen3.8 27B INT8 W8A8 Imatrix 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 Qwen3.8 27B INT8 W8A8 Imatrix

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	123	2
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 FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
Qwen3.5 27B	0K / 55.2 GB	2536294	1028
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342

Note: green Score (e.g. "73.2") means that the model is better than angrykirc/ThinkingCap-Qwen3.8-27B-INT8-W8A8-imatrix.