What are the hardware requirements for Gemma4 31B Opus 4.6 Reasoning?

Gemma4 31B Opus 4.6 Reasoning requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma4 31B Opus 4.6 Reasoning and how large is it?

Gemma4 31B Opus 4.6 Reasoning is developed by kai-os, a model with 31b 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 Gemma4 31B Opus 4.6 Reasoning?

Gemma4 31B Opus 4.6 Reasoning is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma4 31B Opus 4.6 Reasoning by kai-os — VRAM 0.2GB

Name: Gemma4 31B Opus 4.6 Reasoning
Author: kai-os

Gemma4 31B Opus 4.6 Reasoning is an open-source language model by kai-os. Features: 31b LLM, VRAM: 0.2GB, License: apache-2.0, LLM Explorer Score: 0.26.

Adapter Base model:adapter:google/gemm... Base model:google/gemma-4-31b-... Conversational Dataset:crownelius/opus-4.6-re... En Finetuned Gemma Gemma-4 Lora Opus Peft Qlora Reasoning Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/kai-os/gemma4-31b-Opus-4.6-reasoning

Gemma4 31B Opus 4.6 Reasoning Parameters and Internals

LLM Name	Gemma4 31B Opus 4.6 Reasoning
Repository 🤗	https://huggingface.co/kai-os/gemma4-31b-Opus-4.6-reasoning
Base Model(s)	Gemma 4 31B It google/gemma-4-31B-it
Model Size	31b
Required VRAM	0.2 GB
Updated	2026-07-23
Maintainer	kai-os
Model Files	0.2 GB 0.0 GB
Supported Languages	en
Model Architecture	Adapter
License	apache-2.0
Is Biased	none
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	up_proj.linear\|q_proj.linear\|o_proj.linear\|v_proj.linear\|k_proj.linear\|down_proj.linear\|gate_proj.linear
LoRA Alpha	128
LoRA Dropout	0.05
R Param	64

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
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Data Analysis and Insight Generation
Text Generation
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