What are the hardware requirements for Qwen3 32B Mo Posttrained?

Qwen3 32B Mo Posttrained requires approximately 131.6 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 32B Mo Posttrained and how large is it?

Qwen3 32B Mo Posttrained is developed by obalcells, 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 Qwen3 32B Mo Posttrained?

Qwen3 32B Mo Posttrained is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 32B Mo Posttrained by obalcells — VRAM 131.6GB, 40K context

Name: Qwen3 32B Mo Posttrained
Author: obalcells

Qwen3 32B Mo Posttrained is an open-source language model by obalcells. Features: 32b LLM, VRAM: 131.6GB, Context: 40K, LLM Explorer Score: 0.23.

Qwen3 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/obalcells/qwen3-32b-mo-posttrained

Qwen3 32B Mo Posttrained Parameters and Internals

LLM Name	Qwen3 32B Mo Posttrained
Repository 🤗	https://huggingface.co/obalcells/qwen3-32b-mo-posttrained
Model Size	32b
Required VRAM	131.6 GB
Updated	2026-08-04
Maintainer	obalcells
Model Type	qwen3
Model Files	4.5 GB: 1-of-27 4.8 GB: 2-of-27 5.0 GB: 3-of-27 4.8 GB: 4-of-27 5.0 GB: 5-of-27 4.8 GB: 6-of-27 5.0 GB: 7-of-27 4.8 GB: 8-of-27 5.0 GB: 9-of-27 4.8 GB: 10-of-27 5.0 GB: 11-of-27 4.8 GB: 12-of-27 5.0 GB: 13-of-27 4.8 GB: 14-of-27 5.0 GB: 15-of-27 4.8 GB: 16-of-27 5.0 GB: 17-of-27 4.8 GB: 18-of-27 5.0 GB: 19-of-27 4.8 GB: 20-of-27 5.0 GB: 21-of-27 4.8 GB: 22-of-27 5.0 GB: 23-of-27 4.8 GB: 24-of-27 5.0 GB: 25-of-27 4.8 GB: 26-of-27 4.7 GB: 27-of-27
Model Architecture	Qwen3ForCausalLM
Context Length	40960
Model Max Length	40960
Transformers Version	4.57.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float32
Errors	replace

Rank the Qwen3 32B Mo Posttrained 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 32B Mo Posttrained

Best Alternatives	Context / RAM	Downloads	Likes
...ll Qwen3 32B Preview7 QAT 200K	195K / 65.8 GB	10	3
...ll Qwen3 32B Preview6 QAT 200K	195K / 65.8 GB	6	2
...ll Qwen3 32B Preview4 QAT 200K	195K / 65.8 GB	13	2
Qwen3 32B AWorld	128K / 65.8 GB	37	15
Qwen3 32B	40K / 65.8 GB	5411	15
Qwen3 32B	40K / 65.6 GB	6155624	715
OpenThinkerAgent 32B	40K / 65.8 GB	9022	9
Awakening Goedel V2 32B Sft	40K / 65.8 GB	569	0
Awakening Goedel V2 32B Rl	40K / 65.8 GB	565	0
Qwen3 Swallow 32B SFT V0.2	40K / 65.6 GB	24411	0

Note: green Score (e.g. "73.2") means that the model is better than obalcells/qwen3-32b-mo-posttrained.