gemma-4-26B-A4B-it-NVFP4

AtomicChat/gemma-4-26B-A4B-it-NVFP4

gemma-4-26B-A4B-it-NVFP4 is a text generation model from AtomicChat. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.

Downloads · 30 days

27% of all-time downloads

All-time downloads

255

Public

Parameters

25.8B

16.5 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors16.4 GB · 100%

Parameter types

How the weights are stored.

U824.5B · 95%

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Base models

google/gemma-4-26B-A4B-it

Model card

From the Hugging Face model README

<center> <div style="display:flex; justify-content:center; align-items:center; gap:2%; max-width:720px; margin:0 auto;"> <a href="https://atomic.chat" style="flex:0 1 auto; min-width:0;"><img src="https://huggingface.co/AtomicChat/gemma-4-26B-A4B-it-NVFP4/resolve/main/pill_atomic_v3.png" alt="Atomic Chat" style="width:100%; height:auto; max-width:186px;"></a> <a href="https://discord.gg/8wGSsvmg4V" style="flex:0 1 auto; min-width:0;"><img src="https://huggingface.co/AtomicChat/gemma-4-26B-A4B-it-NVFP4/resolve/main/pill_discord_v3.png" alt="Join Discord" style="width:100%; height:auto; max-width:184px;"></a> <a href="https://github.com/AtomicBot-ai/Atomic-Chat" style="flex:0 1 auto; min-width:0;"><img src="https://huggingface.co/AtomicChat/gemma-4-26B-A4B-it-NVFP4/resolve/main/pill_github_v3.png" alt="GitHub" style="width:100%; height:auto; max-width:141px;"></a> <a href="https://x.com/atomic_chat_hq" style="flex:0 1 auto; min-width:0;"><img src="https://huggingface.co/AtomicChat/Qwen3.8-27B-GGUF/resolve/main/pill_x_v3.png" alt="Follow on X" style="width:100%; height:auto; max-width:141px;"></a> </div> <br/> <img src="https://huggingface.co/AtomicChat/gemma-4-26B-A4B-it-NVFP4/resolve/main/hero.png" alt="Gemma 4 26B A4B" style="width:100%; max-width:100%; height:auto; margin-bottom:0.6em;"/> <div style="display:flex; justify-content:center; gap:0.5em;"> <a href="https://huggingface.co/google/gemma-4-26B-A4B-it"><strong>Base model: google/gemma-4-26B-A4B-it</strong></a> </div> </center>

Gemma 4 26B A4B, self-quantized to NVFP4 by Atomic Chat. Built straight from Google's original weights with a per-tensor importance matrix, so this is not a repack of somebody else's files. Runs fully offline.

Highlights

25.2B total / 3.8B active per token parameters: the weights this repo quantizes.
Context length: 256K tokens, as published by Google.
30 layers: Mixture-of-Experts, hybrid sliding-window (1024) and global attention.
Modalities: Text, Image.
Full imatrix ladder: every quant is calibrated with an importance matrix.
Reasoning: All models in the family are designed as highly capable reasoners, with configurable thinking modes.
Diverse & Efficient Architectures: Offers Dense and Mixture-of-Experts (MoE) variants of different sizes for scalable deployment.

[!NOTE] These NVFP4s are self-quantized from the original weights, not a repack. The importance matrix keeps low-bit quants closer to the full-precision model.

Model Overview

Property	Value
Base model	`google/gemma-4-26B-A4B-it`
Parameters	25.2B total / 3.8B active per token
Layers	30
Experts	128 routed (top-8)
Sliding window	1024 tokens
Context length	256K tokens
Vocabulary	262K
Modalities	Text, Image
Architecture	Mixture-of-Experts, 128 experts (top-8), hybrid sliding-window (1024) and global attention, 16 attention heads over 8 KV heads, `Gemma4ForConditionalGeneration`
This repo	NVFP4 weights

Benchmarks

Benchmark	Score
MMLU Pro	82.6%
AIME 2026 no tools	88.3%
LiveCodeBench v6	77.1%
Codeforces ELO	1718
GPQA Diamond	82.3%
Tau2 (average over 3)	68.2%
HLE no tools	8.7%
HLE with search	17.2%
BigBench Extra Hard	64.8%
MMMLU	86.3%
MMMU Pro	73.8%
OmniDocBench 1.5 (average edit distance, lower is better)	0.149
MATH-Vision	82.4%
MedXPertQA MM	58.1%
MRCR v2 8 needle 128k (average)	44.1%

Scores are Google's published results for the base google/gemma-4-26B-A4B-it, not our own measurements. Quantization preserves the large majority of this; Q4_K_M and up stay close to full precision.

Get started

Atomic Chat: search AtomicChat/gemma-4-26B-A4B-it-NVFP4 and hit Use this model.
vLLM: vllm serve AtomicChat/gemma-4-26B-A4B-it-NVFP4 --max-model-len 8192

Best practices

Parameter	Value
temperature	1.0
top_p	0.95
top_k	64

Google's recommended sampling configuration for google/gemma-4-26B-A4B-it.

How these were made

Download google/gemma-4-26B-A4B-it (original weights).
Quantize to NVFP4 with llm-compressor over a calibration corpus.

License

Original model by Google, released under the Apache 2.0 license. Full terms: Apache 2.0. Quantized by Atomic Chat.

Task: Text Generation
Library: transformers
Type: gemma4
License: apache-2.0
Created: Jul 22, 2026
Updated: Oct 28, 2026