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quangvd8x/gemma-3-1b-it-Q4_K_M-GGUF overview

quangvd8x/gemma 3 1b it Q4 K M GGUF This model was converted to GGUF format from google/gemma 3 1b it https://huggingface.co/google/gemma 3 1b it using llama.c…

transformersggufllama-cppgguf-my-repotext-generationbase_model:google/gemma-3-1b-itbase_model:quantized:google/gemma-3-1b-itlicense:gemmaendpoints_compatibleregion:usconversational

Runs locally from ~768.7 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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text-generation
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Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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gemma-3-1b-it-q4_k_m.ggufGGUFQ4_K_M768.7 MBDownload

Model Details

Model IDquangvd8x/gemma-3-1b-it-Q4_K_M-GGUF
Authorquangvd8x
Pipelinetext-generation
Licensegemma
Base modelgoogle/gemma-3-1b-it
Last modified2026-06-12T08:45:08.000Z

Model README

---

license: gemma

library_name: transformers

pipeline_tag: text-generation

extra_gated_heading: Access Gemma on Hugging Face

extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and

agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging

Face and click below. Requests are processed immediately.

extra_gated_button_content: Acknowledge license

base_model: google/gemma-3-1b-it

tags:

  • llama-cpp
  • gguf-my-repo

---

quangvd8x/gemma-3-1b-it-Q4_K_M-GGUF

This model was converted to GGUF format from google/gemma-3-1b-it using llama.cpp via the ggml.ai's GGUF-my-repo space.

Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo quangvd8x/gemma-3-1b-it-Q4_K_M-GGUF --hf-file gemma-3-1b-it-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo quangvd8x/gemma-3-1b-it-Q4_K_M-GGUF --hf-file gemma-3-1b-it-q4_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo quangvd8x/gemma-3-1b-it-Q4_K_M-GGUF --hf-file gemma-3-1b-it-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo quangvd8x/gemma-3-1b-it-Q4_K_M-GGUF --hf-file gemma-3-1b-it-q4_k_m.gguf -c 2048

Run quangvd8x/gemma-3-1b-it-Q4_K_M-GGUF with guIDE

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