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Ling 2.6 Flash MLX Q9 by inferencerlabs

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Ling 2.6 Flash MLX Q9 is an open-source language model by inferencerlabs. Features: LLM, VRAM: 117.2GB, Context: 128K, Quantized, LLM Explorer Score: 0.25.

  Bailing hybrid Base model:inclusionai/ling-2.... Base model:quantized:inclusion...   Conversational   Custom code   En   Mlx   Q9   Quantized   Region:us   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/inferencerlabs/Ling-2.6-flash-MLX-Q9 

Ling 2.6 Flash MLX Q9 Benchmarks

LLME Score: 0.25148
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ling 2.6 Flash MLX Q9 (inferencerlabs/Ling-2.6-flash-MLX-Q9)
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Ling 2.6 Flash MLX Q9 Parameters and Internals

LLM NameLing 2.6 Flash MLX Q9
Repository 🤗https://huggingface.co/inferencerlabs/Ling-2.6-flash-MLX-Q9 
Base Model(s)  inclusionAI/Ling-2.6-flash   inclusionAI/Ling-2.6-flash
Required VRAM117.2 GB
Updated2026-07-20
Maintainerinferencerlabs
Model Typebailing_hybrid
Model Files  9.7 GB: 1-of-12   10.0 GB: 2-of-12   9.8 GB: 3-of-12   10.0 GB: 4-of-12   10.0 GB: 5-of-12   9.8 GB: 6-of-12   10.0 GB: 7-of-12   10.0 GB: 8-of-12   9.8 GB: 9-of-12   10.0 GB: 10-of-12   10.0 GB: 11-of-12   8.1 GB: 12-of-12
Supported Languagesen
Quantization Typeq9
Model ArchitectureBailingMoeV2_5ForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.56.2
Tokenizer ClassTokenizersBackend
Padding Token<|endoftext|>
Vocabulary Size157184
Torch Data Typebfloat16

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Ling 2.6 Flash MLX 9bit128K / 117.2 GB912

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Instruction Following and Task Automation  
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