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MLPerf VS Spell

Compare MLPerf VS Spell and see what are their differences

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MLPerf logo MLPerf

Fair and useful benchmarks for measuring training and inference performance of ML hardware, software, and services.

Spell logo Spell

Deep Learning and AI accessible to everyone
  • MLPerf Landing page
    Landing page //
    2023-08-18
  • Spell Landing page
    Landing page //
    2022-09-23

MLPerf videos

+ Add

SC22: AI Benchmarking & MLPerf™ Webinar

More videos:

  • Review - MLPerf & PyTorch | PyTorch Developer Day 2020
  • Review - Peter Mattson - MLPerf: Driving Innovation by Measuring Performance

Spell videos

+ Add

Love Spells 24 Reviews 💙 My experience with their spells (excited to share)

More videos:

  • Review - SPELL Opulent Decay Album Review | Overkill Reviews
  • Review - LETS REVIEW Spells That Work

Category Popularity

0-100% (relative to MLPerf and Spell)

MLPerf

Spell

Data Science And Machine Learning
17 17%
Data Science And Machine Learning
83% 83
Data Science Notebooks
34 34%
Data Science Notebooks
66% 66
AI
0 0%
AI
100% 100
Machine Learning Tools
100 100%
Machine Learning Tools
0% 0

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What are some alternatives?

When comparing MLPerf and Spell, you can also consider the following products

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

MCenter - Machine Learning Operationalization

Neuton.AI - No-code artificial intelligence for all

5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

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