Ling-3.0-flash#

  • Context Length: 262144

  • Model Name: Ling-3.0-flash

  • Languages: en, zh

  • Abilities: chat, tools, reasoning, hybrid

  • Description: Ling-3.0-flash is a native hybrid-linear reasoning MoE model with 124B total parameters and 5.1B activated parameters per token.

Specifications#

Model Spec 1 (pytorch, 124 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 124

  • Quantizations: none

  • Engines: Transformers

  • Model ID: inclusionAI/Ling-3.0-flash

  • Model Hubs: Hugging Face, ModelScope

Execute the following command to launch the model, remember to replace ${quantization} with your chosen quantization method from the options listed above:

xinference launch --model-engine ${engine} --model-name Ling-3.0-flash --size-in-billions 124 --model-format pytorch --quantization ${quantization}

Model Spec 2 (fp8, 124 Billion)#

  • Model Format: fp8

  • Model Size (in billions): 124

  • Quantizations: FP8

  • Engines: Transformers

  • Model ID: inclusionAI/Ling-3.0-flash-fp8

  • Model Hubs: Hugging Face, ModelScope

Execute the following command to launch the model, remember to replace ${quantization} with your chosen quantization method from the options listed above:

xinference launch --model-engine ${engine} --model-name Ling-3.0-flash --size-in-billions 124 --model-format fp8 --quantization ${quantization}

Model Spec 3 (fp4, 124 Billion)#

  • Model Format: fp4

  • Model Size (in billions): 124

  • Quantizations: FP4

  • Engines:

  • Model ID: inclusionAI/Ling-3.0-flash-fp4

  • Model Hubs: Hugging Face, ModelScope

Execute the following command to launch the model, remember to replace ${quantization} with your chosen quantization method from the options listed above:

xinference launch --model-engine ${engine} --model-name Ling-3.0-flash --size-in-billions 124 --model-format fp4 --quantization ${quantization}

Model Spec 4 (pytorch, 124 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 124

  • Quantizations: Int4

  • Engines: Transformers

  • Model ID: inclusionAI/Ling-3.0-flash-int4

  • Model Hubs: Hugging Face, ModelScope

Execute the following command to launch the model, remember to replace ${quantization} with your chosen quantization method from the options listed above:

xinference launch --model-engine ${engine} --model-name Ling-3.0-flash --size-in-billions 124 --model-format pytorch --quantization ${quantization}