What are the hardware requirements for Sft Qwen Misaligned V3 Round 2 V2?

Sft Qwen Misaligned V3 Round 2 V2 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 Sft Qwen Misaligned V3 Round 2 V2 and how large is it?

Sft Qwen Misaligned V3 Round 2 V2 is developed by obalcells, a model with 32.8b 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 Sft Qwen Misaligned V3 Round 2 V2?

Sft Qwen Misaligned V3 Round 2 V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sft Qwen Misaligned V3 Round 2 V2 by obalcells — VRAM 131.6GB, 40K context

Name: Sft Qwen Misaligned V3 Round 2 V2
Author: obalcells

Sft Qwen Misaligned V3 Round 2 V2 is an open-source language model by obalcells. Features: 32.8b LLM, VRAM: 131.6GB, Context: 40K, LLM Explorer Score: 0.22.

Qwen3 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/obalcells/sft_qwen_misaligned_v3_round_2_v2

Sft Qwen Misaligned V3 Round 2 V2 Parameters and Internals

LLM Name	Sft Qwen Misaligned V3 Round 2 V2
Repository 🤗	https://huggingface.co/obalcells/sft_qwen_misaligned_v3_round_2_v2
Model Size	32.8b
Required VRAM	131.6 GB
Updated	2026-07-24
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 Sft Qwen Misaligned V3 Round 2 V2 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 Sft Qwen Misaligned V3 Round 2 V2

Best Alternatives	Context / RAM	Downloads	Likes
KAT Dev	128K / 65.8 GB	486	218
KAT Dev FP8	128K / 34.5 GB	49	4
...n6HsLp7BhQnSv4XQK4Bys5x8StV1mB	40K / 65.8 GB	510	0
...H5WNQYVTY7SSCbxU3kxqhNybtJeNGb	40K / 65.8 GB	602	0
...vXpbGfnooeuWfr3VueaZrrfWJSou7y	40K / 65.3 GB	562	0
...YCm3AvdiA7dPA34nvB5HwSubVoFREm	40K / 65.7 GB	490	0
...iW6ywTszxd6dKqFoPtKdLQzMkT1kCf	40K / 65.3 GB	372	0
...3uLgTv9xEDiKq2Qx2FVdkuNShfXkwk	40K / 65.7 GB	423	0
...QneuVNKazgCesbu3JDPT3sShv7izBf	40K / 65.5 GB	100	0
...BQQjtS3cXkDV7x46ZUcoUP3pFRGoj4	40K / 65.3 GB	281	0

Note: green Score (e.g. "73.2") means that the model is better than obalcells/sft_qwen_misaligned_v3_round_2_v2.