RedHatAI/gemma-4-12B-it
RedHatAI/gemma-4-12B-it is a any to any model indexed for deployment research. Estimated minimum GPU memory is 32 GB. It is publicly listed on Hugging Face.
What to verify before deployment
- Confirm the exact weight format and quantization.
- Measure memory at your intended context or image size.
- Review model-card limitations and evaluation methodology.
- Test latency and throughput on your target runtime.
Likely commercial-friendly
License metadata is an index signal, not legal advice. Follow the repository license and any model-specific acceptable-use terms.
Verify at the source →More any-to-any models
google/gemma-4-E4B-it
google/gemma-4-E4B-it is a any to any model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
google/gemma-4-E2B-it
google/gemma-4-E2B-it is a any to any model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
google/gemma-4-12B-it
google/gemma-4-12B-it is a any to any model indexed for deployment research. Estimated minimum GPU memory is 32 GB. It is publicly listed on Hugging Face.
unsloth/gemma-4-12B-it-qat-GGUF
unsloth/gemma-4-12B-it-qat-GGUF is a any to any model indexed for deployment research. Estimated minimum GPU memory is 12 GB. It is publicly listed on Hugging Face.
google/gemma-4-12B-it-qat-w4a16-ct
google/gemma-4-12B-it-qat-w4a16-ct is a any to any model indexed for deployment research. Estimated minimum GPU memory is 12 GB. It is publicly listed on Hugging Face.
lmstudio-community/gemma-4-E4B-it-MLX-4bit
lmstudio-community/gemma-4-E4B-it-MLX-4bit is a any to any model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
Operate a GPU cloud or inference API?
Reach developers after they have selected a model and are ready to run it.