What are the hardware requirements for Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX?

Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX requires approximately 0.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX and how large is it?

Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX is developed by 2001Y, 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 Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX?

Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX by 2001Y — VRAM 0.8GB

Name: Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX
Author: 2001Y

Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX is an open-source language model by 2001Y. Features: 27b LLM, VRAM: 0.8GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.34.

2-bit Abliterated Apple-silicon Base model:boldingbuilds/terna... Base model:finetune:boldingbui... Bonsai-2 Conversational En Gguf Ja Mlx Mtp Omlx Pq2 0 Quantized Qwen3 5 Reasoning Region:us Safetensors Speculative-decoding Ternary Uncensored

Model Card on HF 🤗: https://huggingface.co/2001Y/Ternary-Bonsai-2-27B-Abliterated-v2-PQ2_0-MTP-MLX

Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX Parameters and Internals

LLM Name	Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX
Repository 🤗	https://huggingface.co/2001Y/Ternary-Bonsai-2-27B-Abliterated-v2-PQ2_0-MTP-MLX
Base Model(s)	prism-ml/Ternary-Bonsai-2-27B-gguf BoldingBuilds/Ternary-Bonsai-2-27B-Abliterated-v2-PQ2_0-MTP-GGUF prism-ml/Ternary-Bonsai-2-27B-gguf BoldingBuilds/Ternary-Bonsai-2-27B-Abliterated-v2-PQ2_0-MTP-GGUF
Model Size	27b
Required VRAM	0.8 GB
Updated	2026-10-03
Maintainer	2001Y
Model Type	qwen3_5
Model Files	0.0 GB 1.1 GB 1.1 GB 1.1 GB 1.1 GB 1.1 GB 1.1 GB 1.0 GB 0.8 GB 0.8 GB
Supported Languages	en ja
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	BoldingMtpTokenizerFast
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX 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 Ternary Bonsai 2 27B Abliterated V2 PQ2 0 MTP MLX

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...N V1.1 NM DAU NEO MAX MTP GGUF	0K / 0.9 GB	489061	325
Qwen3.8 27B GGUF	0K / 0.9 GB	0	685
... Opus Reasoning Distilled GGUF	0K / 0.9 GB	67921	679
...inkingCap Qwen3.8 27B MIX GGUF	0K / 13.4 GB	1395	7
Swift Qwen3.8 27B MIX GGUF	0K / 0.9 GB	2219	2
...N Blackwell DFlash2 Ultra V1.0	0K / 0.9 GB	3531	3
Ternary Bonsai 2 27B MLX 4bit	0K / 16 GB	1175	2
EleMo V3 Base	0K / 0.9 GB	1989	1
...4 Blackwell DFlash2 Ultra V1.0	0K / 0.9 GB	789	2
...en3.8 27B PristinelyUncensored	0K / 55.5 GB	2244	5

Note: green Score (e.g. "73.2") means that the model is better than 2001Y/Ternary-Bonsai-2-27B-Abliterated-v2-PQ2_0-MTP-MLX.