What are the hardware requirements for Gemma 4 12B It QUASAR W4A16 G64?

Gemma 4 12B It QUASAR W4A16 G64 requires approximately 7.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 4 12B It QUASAR W4A16 G64 and how large is it?

Gemma 4 12B It QUASAR W4A16 G64 is developed by QUASAR-QAT, a model with 12b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Gemma 4 12B It QUASAR W4A16 G64?

Gemma 4 12B It QUASAR W4A16 G64 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 12B It QUASAR W4A16 G64 by QUASAR-QAT — VRAM 7.9GB

Name: Gemma 4 12B It QUASAR W4A16 G64
Author: QUASAR-QAT

Gemma 4 12B It QUASAR W4A16 G64 is an open-source language model by QUASAR-QAT. Features: 12b LLM, VRAM: 7.9GB, License: apache-2.0, LLM Explorer Score: 0.25.

Arxiv:2608.13966 12b 4-bit 4-bit precision Agentic Any-to-any Audio Base model:google/gemma-4-12b-... Base model:quantized:google/ge... Compressed-tensors Conversational En Endpoints compatible Function-calling Gemma Gemma-4 Gemma-4-12b Gemma-4-12b-it Gemma4 Gemma4 unified Google Image-text-to-text Int4 Long-context Multilingual Multimodal Native-qat Qat Quantization-aware-training Quantized Quasar Reasoning Region:us Safetensors Sharded Tensorflow Thinking Tool-calling Vision Vllm Vlm W4a16 Weight-only

Model Card on HF 🤗: https://huggingface.co/QUASAR-QAT/gemma-4-12B-it-QUASAR-W4A16-G64

Gemma 4 12B It QUASAR W4A16 G64 Parameters and Internals

LLM Name	Gemma 4 12B It QUASAR W4A16 G64
Repository 🤗	https://huggingface.co/QUASAR-QAT/gemma-4-12B-it-QUASAR-W4A16-G64
Base Model(s)	Gemma 4 12B It google/gemma-4-12B-it
Model Size	12b
Required VRAM	7.9 GB
Updated	2026-09-14
Maintainer	QUASAR-QAT
Model Type	gemma4_unified
Model Files	4.8 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en
Model Architecture	Gemma4UnifiedForConditionalGeneration
License	apache-2.0
Transformers Version	5.16.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 12B It QUASAR W4A16 G64 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Gemma 4 12B It QUASAR W4A16 G64

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 4 12B It	0K / 23.9 GB	2965396	1417
Gemma 4 12B	0K / 23.9 GB	69628	816
...able5 Composer2.5 V2.3.5x Tau2	0K / 23.9 GB	242415	87
Jev Omni	0K / 23.9 GB	0	223
Gemma 4 12B It	0K / 23.9 GB	146843	15
Gemma 4 12B It NVFP4	0K / 9.3 GB	47579	20
...le5 Composer2.5 V1 Abliterated	0K / 24 GB	30003	1
Gemma 4 12B Aether	0K / 23.9 GB	346	0
Basal Omni 1.0 Max	0K / 23.9 GB	1098	3
Luna Gemma 12B Merged	0K / 10.4 GB	378	0

Note: green Score (e.g. "73.2") means that the model is better than QUASAR-QAT/gemma-4-12B-it-QUASAR-W4A16-G64.