prithivMLmods/gemma-4-12B-it-GGUF overview
gemma 4 12B it GGUF google/gemma 4 12B it from Google DeepMind is a 12B parameter unified, encoder free multimodal model released June 3, 2026, as the first mi…
Runs locally from ~151.6 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| gemma-4-12B-it.BF16.gguf | GGUF | GGUF | 22.20 GB | Download |
| gemma-4-12B-it.F16.gguf | GGUF | GGUF | 22.20 GB | Download |
| gemma-4-12B-it.Q2_K.gguf | GGUF | GGUF | 4.50 GB | Download |
| gemma-4-12B-it.Q3_K_L.gguf | GGUF | GGUF | 6.12 GB | Download |
| gemma-4-12B-it.Q3_K_M.gguf | GGUF | GGUF | 5.67 GB | Download |
| gemma-4-12B-it.Q3_K_S.gguf | GGUF | GGUF | 5.15 GB | Download |
| gemma-4-12B-it.Q4_0.gguf | GGUF | GGUF | 6.50 GB | Download |
| gemma-4-12B-it.Q4_K_M.gguf | GGUF | GGUF | 6.87 GB | Download |
| gemma-4-12B-it.Q4_K_S.gguf | GGUF | GGUF | 6.54 GB | Download |
| gemma-4-12B-it.Q5_0.gguf | GGUF | GGUF | 7.77 GB | Download |
| gemma-4-12B-it.Q5_K_M.gguf | GGUF | GGUF | 7.96 GB | Download |
| gemma-4-12B-it.Q5_K_S.gguf | GGUF | GGUF | 7.77 GB | Download |
| gemma-4-12B-it.Q6_K.gguf | GGUF | GGUF | 9.11 GB | Download |
| gemma-4-12B-it.Q8_0.gguf | GGUF | GGUF | 11.80 GB | Download |
| gemma-4-12B-it.mmproj-bf16.gguf | GGUF | BF16 | 167.0 MB | Download |
| gemma-4-12B-it.mmproj-f16.gguf | GGUF | F16 | 167.0 MB | Download |
| gemma-4-12B-it.mmproj-q8_0.gguf | GGUF | Q8_0 | 151.6 MB | Download |
Model Details
| Model ID | prithivMLmods/gemma-4-12B-it-GGUF |
|---|---|
| Author | prithivMLmods |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | google/gemma-4-12B-it |
| Last modified | 2026-06-07T07:17:07.000Z |
Model README
---
license: apache-2.0
base_model:
- google/gemma-4-12B-it
language:
- en
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- text-generation-inference
- unified
---
gemma-4-12B-it-GGUF
> google/gemma-4-12B-it from Google DeepMind is a 12B-parameter unified, encoder-free multimodal model released June 3, 2026, as the first mid-sized Gemma 4 to feature native audio inputs alongside text, image, and video, processing all modalities by flowing directly into the LLM backbone without separate vision/audio encoders for reduced latency and memory footprint. It delivers performance nearing Gemma 4 26B MoE on standard benchmarks while requiring less than half the total memory (~16GB VRAM or unified memory), making it laptop-ready for consumer hardware with 16GB RAM, Multi-Token Prediction (MTP) drafters for lower latency, and strong agentic reasoning for multi-step workflows. Released under Apache 2.0 with support across the developer ecosystem (Ollama, vLLM, LM Studio), Gemma 4 12B excels at real-time audio/visual understanding, image analysis, content categorization, context compression, and local-first AI applications without API dependency.
Model Files
File Name | Quant Type | File Size | File Link |
|-----------|------------|-----------|-----------|
| gemma-4-12B-it.BF16.gguf | BF16 | 23.8 GB | Download |
| gemma-4-12B-it.F16.gguf | F16 | 23.8 GB | Download |
| gemma-4-12B-it.Q2_K.gguf | Q2_K | 4.83 GB | Download |
| gemma-4-12B-it.Q3_K_L.gguf | Q3_K_L | 6.57 GB | Download |
| gemma-4-12B-it.Q3_K_M.gguf | Q3_K_M | 6.09 GB | Download |
| gemma-4-12B-it.Q3_K_S.gguf | Q3_K_S | 5.53 GB | Download |
| gemma-4-12B-it.Q4_0.gguf | Q4_0 | 6.98 GB | Download |
| gemma-4-12B-it.Q4_K_M.gguf | Q4_K_M | 7.38 GB | Download |
| gemma-4-12B-it.Q4_K_S.gguf | Q4_K_S | 7.02 GB | Download |
| gemma-4-12B-it.Q5_0.gguf | Q5_0 | 8.34 GB | Download |
| gemma-4-12B-it.Q5_K_M.gguf | Q5_K_M | 8.55 GB | Download |
| gemma-4-12B-it.Q5_K_S.gguf | Q5_K_S | 8.34 GB | Download |
| gemma-4-12B-it.Q6_K.gguf | Q6_K | 9.79 GB | Download |
| gemma-4-12B-it.Q8_0.gguf | Q8_0 | 12.7 GB | Download |
| gemma-4-12B-it.mmproj-bf16.gguf | mmproj-bf16 | 175 MB | Download |
| gemma-4-12B-it.mmproj-f16.gguf | mmproj-f16 | 175 MB | Download |
| gemma-4-12B-it.mmproj-q8_0.gguf | mmproj-q8_0 | 159 MB | Download |
llama.cpp
LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp
Run prithivMLmods/gemma-4-12B-it-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models