qwen3.5#

  • Context Length: 262144

  • Model Name: qwen3.5

  • Languages: en, zh

  • Abilities: chat, vision, tools, reasoning, hybrid

  • Description: Over recent months, we have intensified our focus on developing foundation models that deliver exceptional utility and performance. Qwen3.5 represents a significant leap forward, integrating breakthroughs in multimodal learning, architectural efficiency, reinforcement learning scale, and global accessibility to empower developers and enterprises with unprecedented capability and efficiency.

Specifications#

Model Spec 1 (pytorch, 397 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 397

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-397B-A17B

  • 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 qwen3.5 --size-in-billions 397 --model-format pytorch --quantization ${quantization}

Model Spec 2 (fp8, 397 Billion)#

  • Model Format: fp8

  • Model Size (in billions): 397

  • Quantizations: FP8

  • Engines: vLLM, SGLang

  • Model ID: Qwen/Qwen3.5-397B-A17B-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 qwen3.5 --size-in-billions 397 --model-format fp8 --quantization ${quantization}

Model Spec 3 (gptq, 397 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 397

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-397B-A17B-GPTQ-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 qwen3.5 --size-in-billions 397 --model-format gptq --quantization ${quantization}

Model Spec 4 (awq, 397 Billion)#

  • Model Format: awq

  • Model Size (in billions): 397

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: QuantTrio/Qwen3.5-397B-A17B-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 qwen3.5 --size-in-billions 397 --model-format awq --quantization ${quantization}

Model Spec 5 (ggufv2, 397 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 397

  • Quantizations: UD-TQ1_0

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-397B-A17B-GGUF

  • 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 qwen3.5 --size-in-billions 397 --model-format ggufv2 --quantization ${quantization}

Model Spec 6 (mlx, 397 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 397

  • Quantizations: 4bit, 5bit, 6bit, 8bit

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-397B-A17B-{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 qwen3.5 --size-in-billions 397 --model-format mlx --quantization ${quantization}

Model Spec 7 (pytorch, 122 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 122

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-122B-A10B

  • 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 qwen3.5 --size-in-billions 122 --model-format pytorch --quantization ${quantization}

Model Spec 8 (fp8, 122 Billion)#

  • Model Format: fp8

  • Model Size (in billions): 122

  • Quantizations: FP8

  • Engines: vLLM, SGLang

  • Model ID: Qwen/Qwen3.5-122B-A10B-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 qwen3.5 --size-in-billions 122 --model-format fp8 --quantization ${quantization}

Model Spec 9 (gptq, 122 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 122

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-122B-A10B-GPTQ-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 qwen3.5 --size-in-billions 122 --model-format gptq --quantization ${quantization}

Model Spec 10 (awq, 122 Billion)#

  • Model Format: awq

  • Model Size (in billions): 122

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: QuantTrio/Qwen3.5-122B-A10B-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 qwen3.5 --size-in-billions 122 --model-format awq --quantization ${quantization}

Model Spec 11 (ggufv2, 122 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 122

  • Quantizations: UD-IQ1_M, UD-IQ1_S, UD-IQ2_M, UD-IQ2_XXS, UD-IQ3_S, UD-IQ3_XXS

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-122B-A10B-GGUF

  • 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 qwen3.5 --size-in-billions 122 --model-format ggufv2 --quantization ${quantization}

Model Spec 12 (mlx, 122 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 122

  • Quantizations: 4bit, 5bit, 6bit, 8bit, bf16

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-122B-A10B-{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 qwen3.5 --size-in-billions 122 --model-format mlx --quantization ${quantization}

Model Spec 13 (pytorch, 35 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 35

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-35B-A3B

  • 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 qwen3.5 --size-in-billions 35 --model-format pytorch --quantization ${quantization}

Model Spec 14 (fp8, 35 Billion)#

  • Model Format: fp8

  • Model Size (in billions): 35

  • Quantizations: FP8

  • Engines: vLLM, SGLang

  • Model ID: Qwen/Qwen3.5-35B-A3B-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 qwen3.5 --size-in-billions 35 --model-format fp8 --quantization ${quantization}

Model Spec 15 (gptq, 35 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 35

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-35B-A3B-GPTQ-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 qwen3.5 --size-in-billions 35 --model-format gptq --quantization ${quantization}

Model Spec 16 (awq, 35 Billion)#

  • Model Format: awq

  • Model Size (in billions): 35

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: QuantTrio/Qwen3.5-35B-A3B-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 qwen3.5 --size-in-billions 35 --model-format awq --quantization ${quantization}

Model Spec 17 (ggufv2, 35 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 35

  • Quantizations: MXFP4_MOE, Q3_K_M, Q3_K_S, Q4_K_M, Q4_K_S, Q5_K_M, Q5_K_S, Q6_K, Q8_0, UD-IQ1_M, UD-IQ2_M, UD-IQ2_XXS, UD-IQ3_S, UD-IQ3_XXS, UD-IQ4_NL, UD-IQ4_XS, UD-Q2_K_XL, UD-Q3_K_XL, UD-Q4_K_L, UD-Q4_K_XL, UD-Q5_K_XL, UD-Q6_K_S, UD-Q6_K_XL, UD-Q8_K_XL

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-35B-A3B-GGUF

  • 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 qwen3.5 --size-in-billions 35 --model-format ggufv2 --quantization ${quantization}

Model Spec 18 (mlx, 35 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 35

  • Quantizations: 4bit, 5bit, 6bit, 8bit, bf16

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-35B-A3B-{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 qwen3.5 --size-in-billions 35 --model-format mlx --quantization ${quantization}

Model Spec 19 (pytorch, 27 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 27

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-27B

  • 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 qwen3.5 --size-in-billions 27 --model-format pytorch --quantization ${quantization}

Model Spec 20 (fp8, 27 Billion)#

  • Model Format: fp8

  • Model Size (in billions): 27

  • Quantizations: FP8

  • Engines: vLLM, SGLang

  • Model ID: Qwen/Qwen3.5-27B-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 qwen3.5 --size-in-billions 27 --model-format fp8 --quantization ${quantization}

Model Spec 21 (gptq, 27 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 27

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-27B-GPTQ-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 qwen3.5 --size-in-billions 27 --model-format gptq --quantization ${quantization}

Model Spec 22 (awq, 27 Billion)#

  • Model Format: awq

  • Model Size (in billions): 27

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: QuantTrio/Qwen3.5-27B-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 qwen3.5 --size-in-billions 27 --model-format awq --quantization ${quantization}

Model Spec 23 (ggufv2, 27 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 27

  • Quantizations: IQ4_NL, IQ4_XS, Q3_K_M, Q3_K_S, Q4_0, Q4_1, Q4_K_M, Q4_K_S, Q5_K_M, Q5_K_S, Q6_K, Q8_0, UD-IQ2_M, UD-IQ2_XXS, UD-IQ3_XXS, UD-Q2_K_XL, UD-Q3_K_XL, UD-Q4_K_XL, UD-Q5_K_XL, UD-Q6_K_XL, UD-Q8_K_XL

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-27B-GGUF

  • 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 qwen3.5 --size-in-billions 27 --model-format ggufv2 --quantization ${quantization}

Model Spec 24 (mlx, 27 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 27

  • Quantizations: 4bit, 5bit, 6bit, 8bit, bf16, mxfp8

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-27B-{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 qwen3.5 --size-in-billions 27 --model-format mlx --quantization ${quantization}

Model Spec 25 (pytorch, 9 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 9

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-9B

  • 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 qwen3.5 --size-in-billions 9 --model-format pytorch --quantization ${quantization}

Model Spec 26 (awq, 9 Billion)#

  • Model Format: awq

  • Model Size (in billions): 9

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: QuantTrio/Qwen3.5-9B-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 qwen3.5 --size-in-billions 9 --model-format awq --quantization ${quantization}

Model Spec 27 (ggufv2, 9 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 9

  • Quantizations: BF16, IQ4_NL, IQ4_XS, Q3_K_M, Q3_K_S, Q4_0, Q4_1, Q4_K_M, Q4_K_S, Q5_K_M, Q5_K_S, Q6_K, Q8_0, UD-IQ2_M, UD-IQ2_XXS, UD-IQ3_XXS, UD-Q2_K_XL, UD-Q3_K_XL, UD-Q4_K_XL, UD-Q5_K_XL, UD-Q6_K_XL, UD-Q8_K_XL

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-9B-GGUF

  • 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 qwen3.5 --size-in-billions 9 --model-format ggufv2 --quantization ${quantization}

Model Spec 28 (mlx, 9 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 9

  • Quantizations: 4bit, 5bit, 6bit, 8bit, bf16

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-9B-{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 qwen3.5 --size-in-billions 9 --model-format mlx --quantization ${quantization}

Model Spec 29 (pytorch, 4 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 4

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-4B

  • 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 qwen3.5 --size-in-billions 4 --model-format pytorch --quantization ${quantization}

Model Spec 30 (awq, 4 Billion)#

  • Model Format: awq

  • Model Size (in billions): 4

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: QuantTrio/Qwen3.5-4B-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 qwen3.5 --size-in-billions 4 --model-format awq --quantization ${quantization}

Model Spec 31 (ggufv2, 4 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 4

  • Quantizations: BF16, IQ4_NL, IQ4_XS, Q3_K_M, Q3_K_S, Q4_0, Q4_1, Q4_K_M, Q4_K_S, Q5_K_M, Q5_K_S, Q6_K, Q8_0, UD-IQ2_M, UD-IQ2_XXS, UD-IQ3_XXS, UD-Q2_K_XL, UD-Q3_K_XL, UD-Q4_K_XL, UD-Q5_K_XL, UD-Q6_K_XL, UD-Q8_K_XL

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-4B-GGUF

  • 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 qwen3.5 --size-in-billions 4 --model-format ggufv2 --quantization ${quantization}

Model Spec 32 (mlx, 4 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 4

  • Quantizations: 3bit, 4bit, 6bit, 8bit

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-4B-{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 qwen3.5 --size-in-billions 4 --model-format mlx --quantization ${quantization}

Model Spec 33 (pytorch, 2 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 2

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-2B

  • 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 qwen3.5 --size-in-billions 2 --model-format pytorch --quantization ${quantization}

Model Spec 34 (awq, 2 Billion)#

  • Model Format: awq

  • Model Size (in billions): 2

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: QuantTrio/Qwen3.5-2B-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 qwen3.5 --size-in-billions 2 --model-format awq --quantization ${quantization}

Model Spec 35 (ggufv2, 2 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 2

  • Quantizations: BF16, IQ4_NL, IQ4_XS, Q3_K_M, Q3_K_S, Q4_0, Q4_1, Q4_K_M, Q4_K_S, Q5_K_M, Q5_K_S, Q6_K, Q8_0, UD-IQ2_M, UD-IQ2_XXS, UD-IQ3_XXS, UD-Q2_K_XL, UD-Q3_K_XL, UD-Q4_K_XL, UD-Q5_K_XL, UD-Q6_K_XL, UD-Q8_K_XL

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-2B-GGUF

  • 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 qwen3.5 --size-in-billions 2 --model-format ggufv2 --quantization ${quantization}

Model Spec 36 (mlx, 2 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 2

  • Quantizations: 3bit, 4bit, 5bit, 6bit, 8bit, bf16, mxfp4, mxfp8, nvfp4

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-2B-{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 qwen3.5 --size-in-billions 2 --model-format mlx --quantization ${quantization}

Model Spec 37 (pytorch, 0_8 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 0_8

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: Qwen/Qwen3.5-0.8B

  • 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 qwen3.5 --size-in-billions 0_8 --model-format pytorch --quantization ${quantization}

Model Spec 38 (ggufv2, 0_8 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 0_8

  • Quantizations: BF16, IQ4_NL, IQ4_XS, Q3_K_M, Q3_K_S, Q4_0, Q4_1, Q4_K_M, Q4_K_S, Q5_K_M, Q5_K_S, Q6_K, Q8_0, UD-IQ2_M, UD-IQ2_XXS, UD-IQ3_XXS, UD-Q2_K_XL, UD-Q3_K_XL, UD-Q4_K_XL, UD-Q5_K_XL, UD-Q6_K_XL, UD-Q8_K_XL

  • Engines: llama.cpp

  • Model ID: unsloth/Qwen3.5-0.8B-GGUF

  • 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 qwen3.5 --size-in-billions 0_8 --model-format ggufv2 --quantization ${quantization}

Model Spec 39 (mlx, 0_8 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 0_8

  • Quantizations: 3bit, 4bit, 5bit, 6bit, 8bit, bf16, mxfp4, mxfp8, nvfp4

  • Engines: MLX

  • Model ID: mlx-community/Qwen3.5-0.8B-{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 qwen3.5 --size-in-billions 0_8 --model-format mlx --quantization ${quantization}