inclusionAI/ZoomGain-9B-GGUF
inclusionAI/ZoomGain-9B-GGUF
The GGUF format weights for inclusionAI/ZoomGain-9B have been released, converted using llama.cpp, with the language model in FP16, Q8_0, Q4_K_M. The visual encoder and projector (mmproj) also adopt this quantization scheme. Both the language model and mmproj files need to be provided for image input, supporting CLI inference (llama-mtmd-cli) and Web Chat (llama-server) deployment.
GGUF-format weights for ZoomGain-9B, converted with llama.cpp.
- Language model: FP16, Q8_0, Q4_K_M.
- Vision encoder and projector (
mmproj): FP16, Q8_0, Q4_K_M.
For image input, provide both the language model and the corresponding mmproj file.
CLI Inference (llama-mtmd-cli)
llama-mtmd-cli \
-m ZoomGain-9B-Q8_0.gguf \
--mmproj mmproj-ZoomGain-9B-Q8_0.gguf \
--image /path/to/image.jpg \
-p "Describe this image." \
--temp 0 -n 2048
Web Chat (llama-server)
llama-server \
-m ZoomGain-9B-Q8_0.gguf \
--mmproj mmproj-ZoomGain-9B-Q8_0.gguf \
--host 127.0.0.1 --port 8080
Replace Q8_0 with F16 or Q4_K_M to use another precision.
Use a llama.cpp build with Qwen3.5 multimodal support. Quantization can affect accuracy.
Source: Ant Group inclusionAI · Hugging Face new models · huggingface.co