gemma-4-26B-A4B-it-mxfp8-mlx

2.5K
license:apache-2.0
by
nightmedia
Image Model
OTHER
26B params
New
3K downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
59GB+ RAM
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
25GB+ RAM

Training Data Analysis

🟡 Average (4.3/10)

Researched training datasets used by gemma-4-26B-A4B-it-mxfp8-mlx with quality assessment

Specialized For

general
science
multilingual
reasoning

Training Datasets (3)

common crawl
🔴 2.5/10
general
science
Key Strengths
  • •Scale and Accessibility: At 9.5+ petabytes, Common Crawl provides unprecedented scale for training d...
  • •Diversity: The dataset captures billions of web pages across multiple domains and content types, ena...
  • •Comprehensive Coverage: Despite limitations, Common Crawl attempts to represent the broader web acro...
Considerations
  • •Biased Coverage: The crawling process prioritizes frequently linked domains, making content from dig...
  • •Large-Scale Problematic Content: Contains significant amounts of hate speech, pornography, violent c...
wikipedia
🟡 5/10
science
multilingual
Key Strengths
  • •High-Quality Content: Wikipedia articles are subject to community review, fact-checking, and citatio...
  • •Multilingual Coverage: Available in 300+ languages, enabling training of models that understand and ...
  • •Structured Knowledge: Articles follow consistent formatting with clear sections, allowing models to ...
Considerations
  • •Language Inequality: Low-resource language editions have significantly lower quality, fewer articles...
  • •Biased Coverage: Reflects biases in contributor demographics; topics related to Western culture and ...
arxiv
🟡 5.5/10
science
reasoning
Key Strengths
  • •Scientific Authority: Peer-reviewed content from established repository
  • •Domain-Specific: Specialized vocabulary and concepts
  • •Mathematical Content: Includes complex equations and notation
Considerations
  • •Specialized: Primarily technical and mathematical content
  • •English-Heavy: Predominantly English-language papers

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

gemma-4-26B-A4B-it-mxfp8-mlxbrainwaves
arc   arc/e boolq hswag obkqa piqa  wino
mxfp8    0.454,0.598,0.871,0.582,0.394,0.723,0.645
mxfp4    0.462,0.596,0.855,0.578,0.378,0.723,0.637
qx86-hi  0.472,0.605,0.873,0.565,0.386,0.712,0.644
qx64-hi  0.472,0.621,0.866,0.564,0.382,0.717,0.637

Perplexity               Peak Memory   Tokens/sec
mxfp8   103.904 ± 1.765   33.28 GB      880
mxfp4   123.621 ± 2.121   20.66 GB     1266
qx86-hi  75.542 ± 1.247   29.23 GB     1145
qx64-hi  98.161 ± 1.645   22.92 GB     1135
brainwaves
arc   arc/e boolq hswag obkqa piqa  wino

TeichAI/gemma-4-26B-A4B-it-Claude-Opus-Distill
qx86-hi  0.433,0.522,0.468,0.506,0.370,0.687,0.612
Instruct
qx86-hi  0.564,0.763,0.861,0.657,0.450,0.771,0.680

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