AtomicChat

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

README

License: apache-2.0

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

Table with columns: Property, Value
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`

Benchmarks

Table with columns: Benchmark, Score
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%

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

Table with columns: Parameter, Value
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.

Available on FriendliAI

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Model Details

Model Provider

AtomicChat

Model Tree

Base

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

Quantized

this model

Input Modalities

TextImage

Output Modalities

Text

Supported Functionality

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