Qwen3-VL-Instruct#
Context Length: 262144
Model Name: Qwen3-VL-Instruct
Languages: en, zh
Abilities: chat, vision, tools
Description: Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date.
Specifications#
Model Spec 1 (pytorch, 235 Billion)#
Model Format: pytorch
Model Size (in billions): 235
Quantizations: none
Engines: vLLM, Transformers
Model ID: Qwen/Qwen3-VL-235B-A22B-Instruct
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 Qwen3-VL-Instruct --size-in-billions 235 --model-format pytorch --quantization ${quantization}
Model Spec 2 (fp8, 235 Billion)#
Model Format: fp8
Model Size (in billions): 235
Quantizations: fp8
Engines: vLLM, Transformers
Model ID: Qwen/Qwen3-VL-235B-A22B-Instruct-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 Qwen3-VL-Instruct --size-in-billions 235 --model-format fp8 --quantization ${quantization}
Model Spec 3 (awq, 235 Billion)#
Model Format: awq
Model Size (in billions): 235
Quantizations: Int4
Engines: vLLM, Transformers
Model ID: QuantTrio/Qwen3-VL-235B-A22B-Instruct-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 Qwen3-VL-Instruct --size-in-billions 235 --model-format awq --quantization ${quantization}
Model Spec 4 (pytorch, 30 Billion)#
Model Format: pytorch
Model Size (in billions): 30
Quantizations: none
Engines: vLLM, Transformers
Model ID: Qwen/Qwen3-VL-30B-A3B-Instruct
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 Qwen3-VL-Instruct --size-in-billions 30 --model-format pytorch --quantization ${quantization}
Model Spec 5 (fp8, 30 Billion)#
Model Format: fp8
Model Size (in billions): 30
Quantizations: fp8
Engines: vLLM, Transformers
Model ID: Qwen/Qwen3-VL-30B-A3B-Instruct-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 Qwen3-VL-Instruct --size-in-billions 30 --model-format fp8 --quantization ${quantization}
Model Spec 6 (awq, 30 Billion)#
Model Format: awq
Model Size (in billions): 30
Quantizations: 4bit, 8bit
Engines: vLLM, Transformers
Model ID: cpatonn/Qwen3-VL-30B-A3B-Instruct-AWQ-{quantization}
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 Qwen3-VL-Instruct --size-in-billions 30 --model-format awq --quantization ${quantization}