What are the hardware requirements for Tqwendo 36B?

Tqwendo 36B requires approximately 71.7 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tqwendo 36B and how large is it?

Tqwendo 36B is developed by nisten, a model with 32b 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 Tqwendo 36B?

Tqwendo 36B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tqwendo 36B by nisten — VRAM 71.7GB, 32K context

Name: Tqwendo 36B
Author: nisten

Tqwendo 36B is an open-source language model by nisten. Features: 32b LLM, VRAM: 71.7GB, Context: 32K, License: mit, Instruction-Based, Code Generating, LLM Explorer Score: 0.26.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-... Code Codegen Conversational Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/nisten/tqwendo-36b

Tqwendo 36B Parameters and Internals

LLM Name	Tqwendo 36B
Repository 🤗	https://huggingface.co/nisten/tqwendo-36b
Base Model(s)	Qwen/Qwen2.5-Coder-32B-Instruct huihui-ai/Qwen2.5-Coder-32B-Instruct-abliterated Qwen/Qwen2.5-Coder-32B-Instruct huihui-ai/Qwen2.5-Coder-32B-Instruct-abliterated
Model Size	32b
Required VRAM	71.7 GB
Updated	2026-08-07
Maintainer	nisten
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-15 5.0 GB: 2-of-15 4.9 GB: 3-of-15 4.9 GB: 4-of-15 4.9 GB: 5-of-15 4.9 GB: 6-of-15 4.9 GB: 7-of-15 4.9 GB: 8-of-15 4.9 GB: 9-of-15 4.9 GB: 10-of-15 4.8 GB: 11-of-15 5.0 GB: 12-of-15 4.9 GB: 13-of-15 4.9 GB: 14-of-15 2.9 GB: 15-of-15
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.45.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Tqwendo 36B 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 Tqwendo 36B

Best Alternatives	Context / RAM	Downloads	Likes
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	9	2
Qwen2.5 32B YOYO MIX	128K / 65.7 GB	8	2
Qwen2.5 Coder 32B YOYO	128K / 65.8 GB	8	2
QwQ Qwen2.5 Coder Instruct 32B	128K / 65.8 GB	43	0
QwQenSeek Coder	128K / 65.7 GB	26	5
Rombos Coder V2.5 Qwen 32B	128K / 65.8 GB	10	19
Tessa T1 32B	117K / 65.8 GB	12	22
UIGEN T1.5 32B	117K / 65.8 GB	12	13
Qwen2.5 Coder 32B Instruct	32K / 65.8 GB	1265226	2087
Qwen2.5 Coder 32B Instruct	32K / 65.8 GB	2100	7

Note: green Score (e.g. "73.2") means that the model is better than nisten/tqwendo-36b.