Bonsai 27B MLX BF16 Config Repaired by TiGa-RCE

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Bonsai 27B MLX BF16 Config Repaired is an open-source language model by TiGa-RCE. Features: 27b LLM, VRAM: 53.5GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.29.

  Apple-silicon Base model:finetune:prism-ml/b... Base model:prism-ml/bonsai-27b...   Bonsai   Conversational   En   Experimental   Gguf   Mlx   Quantized   Qwen3.6   Qwen3 5   Region:us   Safetensors   Sharded   Tensorflow

Bonsai 27B MLX BF16 Config Repaired Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Bonsai 27B MLX BF16 Config Repaired Parameters and Internals

LLM NameBonsai 27B MLX BF16 Config Repaired
Repository 🤗https://huggingface.co/TiGa-RCE/Bonsai-27B-MLX-BF16-Config-Repaired 
Base Model(s)  prism-ml/Bonsai-27B-gguf   prism-ml/Bonsai-27B-gguf
Model Size27b
Required VRAM53.5 GB
Updated2026-07-21
MaintainerTiGa-RCE
Model Typeqwen3_5
Model Files  5.2 GB: 1-of-11   5.3 GB: 2-of-11   5.3 GB: 3-of-11   5.3 GB: 4-of-11   5.3 GB: 5-of-11   5.3 GB: 6-of-11   5.3 GB: 7-of-11   5.3 GB: 8-of-11   5.3 GB: 9-of-11   3.4 GB: 10-of-11   2.5 GB: 11-of-11
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureQwen3_5ForConditionalGeneration
Licenseapache-2.0
Model Max Length262144
Transformers Version4.57.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Errorsreplace

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... Opus Reasoning Distilled GGUF0K / 10.7 GB990748
Qwen3.6 27B OptiQ 4bit256K / 18.7 GB1306559
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Qwen3.6 27B UD Q3 K XL Mlx0K / 18.7 GB3953
Apax Q4 K M0K / 55.2 GB120
MLX Qwopus3.5 27B V3 6bit0K / 21.8 GB1413
Qwen3.5 27B 4bit DWQ0K / 15.2 GB716
... Opus Reasoning Distilled 4bit0K / 15.1 GB1308
...e 4.6 Opus Reasoning Distilled0K / 55.2 GB1510562890
Qwen3.5 27B0K / 54.7 GB1345615
Note: green Score (e.g. "73.2") means that the model is better than TiGa-RCE/Bonsai-27B-MLX-BF16-Config-Repaired.

Rank the Bonsai 27B MLX BF16 Config Repaired Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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  

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Release v20260328a