InternVL3#

  • Context Length: 8192

  • Model Name: InternVL3

  • Languages: en, zh

  • Abilities: chat, vision

  • Description: InternVL3, an advanced multimodal large language model (MLLM) series that demonstrates superior overall performance.

Specifications#

Model Spec 1 (pytorch, 1 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 1

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-1B

  • 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 InternVL3 --size-in-billions 1 --model-format pytorch --quantization ${quantization}

Model Spec 2 (awq, 1 Billion)#

  • Model Format: awq

  • Model Size (in billions): 1

  • Quantizations: Int4

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-1B-AWQ

  • 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 InternVL3 --size-in-billions 1 --model-format awq --quantization ${quantization}

Model Spec 3 (pytorch, 2 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 2

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-2B

  • 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 InternVL3 --size-in-billions 2 --model-format pytorch --quantization ${quantization}

Model Spec 4 (awq, 2 Billion)#

  • Model Format: awq

  • Model Size (in billions): 2

  • Quantizations: Int4

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-2B-AWQ

  • 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 InternVL3 --size-in-billions 2 --model-format awq --quantization ${quantization}

Model Spec 5 (pytorch, 8 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 8

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-8B

  • 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 InternVL3 --size-in-billions 8 --model-format pytorch --quantization ${quantization}

Model Spec 6 (awq, 8 Billion)#

  • Model Format: awq

  • Model Size (in billions): 8

  • Quantizations: Int4

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-8B-AWQ

  • 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 InternVL3 --size-in-billions 8 --model-format awq --quantization ${quantization}

Model Spec 7 (pytorch, 9 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 9

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-9B

  • 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 InternVL3 --size-in-billions 9 --model-format pytorch --quantization ${quantization}

Model Spec 8 (awq, 9 Billion)#

  • Model Format: awq

  • Model Size (in billions): 9

  • Quantizations: Int4

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-9B-AWQ

  • 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 InternVL3 --size-in-billions 9 --model-format awq --quantization ${quantization}

Model Spec 9 (pytorch, 14 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 14

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-14B

  • 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 InternVL3 --size-in-billions 14 --model-format pytorch --quantization ${quantization}

Model Spec 10 (awq, 14 Billion)#

  • Model Format: awq

  • Model Size (in billions): 14

  • Quantizations: Int4

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-14B-AWQ

  • 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 InternVL3 --size-in-billions 14 --model-format awq --quantization ${quantization}

Model Spec 11 (pytorch, 38 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 38

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-38B

  • 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 InternVL3 --size-in-billions 38 --model-format pytorch --quantization ${quantization}

Model Spec 12 (awq, 38 Billion)#

  • Model Format: awq

  • Model Size (in billions): 38

  • Quantizations: Int4

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-38B-AWQ

  • 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 InternVL3 --size-in-billions 38 --model-format awq --quantization ${quantization}

Model Spec 13 (pytorch, 78 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 78

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-78B

  • 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 InternVL3 --size-in-billions 78 --model-format pytorch --quantization ${quantization}

Model Spec 14 (awq, 78 Billion)#

  • Model Format: awq

  • Model Size (in billions): 78

  • Quantizations: Int4

  • Engines: vLLM, Transformers

  • Model ID: OpenGVLab/InternVL3-78B-AWQ

  • 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 InternVL3 --size-in-billions 78 --model-format awq --quantization ${quantization}