gemma-4#

  • Context Length: 262144

  • Model Name: gemma-4

  • Languages: en, zh

  • Abilities: generate, chat, reasoning, audio, vision, hybrid

  • Description: Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on small models) and generating text output.

Specifications#

Model Spec 1 (pytorch, 2 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 2

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: google/gemma-4-E2B-it

  • 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 gemma-4 --size-in-billions 2 --model-format pytorch --quantization ${quantization}

Model Spec 2 (pytorch, 4 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 4

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: google/gemma-4-E4B-it

  • 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 gemma-4 --size-in-billions 4 --model-format pytorch --quantization ${quantization}

Model Spec 3 (pytorch, 31 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 31

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: google/gemma-4-31B-it

  • 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 gemma-4 --size-in-billions 31 --model-format pytorch --quantization ${quantization}

Model Spec 4 (fp4, 31 Billion)#

  • Model Format: fp4

  • Model Size (in billions): 31

  • Quantizations: FP4

  • Engines: vLLM, Transformers

  • Model ID: nvidia/Gemma-4-31B-IT-NVFP4

  • 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 gemma-4 --size-in-billions 31 --model-format fp4 --quantization ${quantization}

Model Spec 5 (pytorch, 26 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 26

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: google/gemma-4-26B-A4B-it

  • 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 gemma-4 --size-in-billions 26 --model-format pytorch --quantization ${quantization}

Model Spec 6 (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-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/gemma-4-E2B-it-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 gemma-4 --size-in-billions 2 --model-format ggufv2 --quantization ${quantization}

Model Spec 7 (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-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/gemma-4-E4B-it-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 gemma-4 --size-in-billions 4 --model-format ggufv2 --quantization ${quantization}

Model Spec 8 (ggufv2, 31 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 31

  • 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-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/gemma-4-31B-it-GGUF

  • Model Hubs: Hugging Face

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 gemma-4 --size-in-billions 31 --model-format ggufv2 --quantization ${quantization}

Model Spec 9 (ggufv2, 26 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 26

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

  • Engines: llama.cpp

  • Model ID: unsloth/gemma-4-26B-A4B-it-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 gemma-4 --size-in-billions 26 --model-format ggufv2 --quantization ${quantization}

Model Spec 10 (mlx, 2 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 2

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

  • Engines: MLX

  • Model ID: mlx-community/gemma-4-e2b-it-{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 gemma-4 --size-in-billions 2 --model-format mlx --quantization ${quantization}

Model Spec 11 (mlx, 4 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 4

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

  • Engines: MLX

  • Model ID: mlx-community/gemma-4-e4b-it-{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 gemma-4 --size-in-billions 4 --model-format mlx --quantization ${quantization}

Model Spec 12 (mlx, 31 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 31

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

  • Engines: MLX

  • Model ID: mlx-community/gemma-4-31b-it-{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 gemma-4 --size-in-billions 31 --model-format mlx --quantization ${quantization}

Model Spec 13 (mlx, 26 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 26

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

  • Engines: MLX

  • Model ID: mlx-community/gemma-4-26b-a4b-it-{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 gemma-4 --size-in-billions 26 --model-format mlx --quantization ${quantization}