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>Fast.ai vs Modal

Fast.ai AI Company Profile & RankingsModal AI Company Profile & Rankings

AI Activity Comparison

Fast.ai

Fast.ai is a non-profit research group focused on deep learning and artificial intelligence, founded in 2016 by Jeremy Howard and Rachel Thomas. Its core mission is to democratize deep learning through education. The organization is best known for providing a free massive open online course (MOOC), 'Practical Deep Learning for Coders,' which requires only a knowledge of Python. The course covers topics including image classification, natural language processing, and various deep learning architectures. In 2018, students from the program won the CIFAR-10 image classification benchmark in Stanford’s DAWNBench competition. The group continues its research and educational efforts to make deep learning more accessible.

Modal

Modal, formerly known as Next Technology Inc., is a San Francisco-based technology company. It initially developed software that enabled automotive dealerships to sell new and used cars directly to consumers through their websites. The company was founded in 2015 with backing from Khosla Ventures and participated in the Y Combinator seed accelerator program in 2016. It achieved $1 million in annual recurring revenue within ten months of its official launch. Currently, Modal is focused on artificial intelligence, specifically on developing and serving large language model (LLM) workloads, and is ranked within the AI industry.

Data updated: • Live

Fast.ai versus Modal: Live 2026 Comparison

Based on real-time data, Modal outperforms Fast.ai across both activity (1 vs 0 events this week) and community sentiment (60% vs 30%). This comparison draws on 1 tracked events from the past 7 days — including product launches, research papers, and community discussions — scored through our 5-dimension scoring methodology. Our Hype Gap analysis shows Modal has more authentic positioning (gap: 2.0) compared to Fast.ai (10.0). Data refreshes every 5 minutes. Compare other AI companies →

Fast.ai vs Modal: Key Signals

Activity:Modal 1 events/wk vs Fast.ai 0
Sentiment:Modal 60% vs Fast.ai 30%
Rank gap:#117 vs #119 (2 positions apart)
Hype gap:Fast.ai +10.0 vs Modal +2.0
Score:Fast.ai 9 vs Modal 8

Data refreshes every 5 minutes. Compare other companies →

Fast.ai vs Modal: Head-to-Head

Comparison of key metrics between Fast.ai and Modal
MetricFast.aiModal
Rank#117#119
Overall Score8.58.2
7-Day Events01
30-Day Events03
Sentiment30%60%
Momentum
7d vs 30d velocity
0%0%
Hype Score10.05.1
Reality Score0.03.1
Hype Gap+10.0+2.0

📊 Visual Comparison

Compare 5 key metrics on a 0-100 scale. Larger area = stronger overall performance.

Fast.ai
Modal
Activity
0vs1
Sentiment
30vs60
Score
9vs8
Momentum
50vs50
Confidence
0vs0

Metric Definitions:

Activity: Weekly GitHub events (max 200 = 100)
Sentiment: Community sentiment (0-100)
Score: Overall ranking score
Momentum: Rank movement trend (50 = neutral)
Confidence: Data confidence level (0-100)

What Separates Fast.ai from Modal

Who Ships Faster: Modal or Fast.ai?

Modal logged 1 events this week vs Fast.ai's 0 — a significant difference in product launches, research papers, and code commits.

What Users Think of Modal vs Fast.ai

Modal has 60% positive sentiment vs Fast.ai's 30%. That 30-point gap is significant — it signals stronger user satisfaction and fewer community complaints about Modal.

Does Modal Deliver on Its Promises?

Modal's hype gap of 2.0 vs Fast.ai's 10.0 means Modal delivers on its promises — marketing claims closely match actual capabilities.

Where Fast.ai and Modal Rank

Fast.ai at #117 outranks Modal at #119 among 2,800+ AI companies. Just 2 ranks apart — a single product launch could flip this ranking.

Fast.ai vs Modal: Momentum Trend

Both companies show stable or declining momentum, suggesting a period of consolidation rather than rapid expansion.

Latest Signals: Fast.ai vs Modal

Latest tracked events for each company — product launches, research papers, community discussions, and more.

Fast.ai(0 events this week)

  • GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations

    ArXiv AI (cs.AI)
  • GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations

    ArXiv Machine Learning (cs.LG)
  • [D] Classification of low resource language using Deep learning

    Reddit - r/MachineLearning Hot
  • Fine-Grained Emotion Detection on GoEmotions: Experimental Comparison of Classical Machine Learning, BiLSTM, and Transformer Models

    ArXiv NLP (cs.CL)
  • BERTs that chat: turn any BERT into a chatbot with dLLM

    Reddit - r/LocalLLaMA New
View all Fast.ai signals →

Modal(1 events this week)

  • GitHub - TheFloatingString/sam3-on-modal: Running SAM-3 inference on Modal GPUs.

    Hacker News Newest
  • Rolling your own serverless OCR in 40 lines of code | Christopher Krapu

    Hacker News Front Page
  • We cut GPU costs ~3× by migrating from Azure Container Apps to Modal. Here's exactly how.

    Reddit - r/deeplearning
  • Serving accelerated FLUX models on Modal

    Hacker News Newest
  • Three types of LLM workloads and how to serve them

    AI/ML Stories
View all Modal signals →

Analysis: Fast.ai vs Modal

Fast.ai and Modal are virtually tied in the Sector HQ rankings, separated by just 2 positions — making this one of the most competitive matchups in AI.

Modal is shipping faster with 1 events this week, compared to Fast.ai's 0.

Community sentiment diverges sharply: Modal at 60% positive vs Fast.ai's 30%. Modal maintains more authentic positioning with a hype gap of 2.0, compared to Fast.ai's 10.0 — a key signal for evaluating long-term reliability.

Watch for: Fast.ai's latest signal ("GECOBench: A Gender-Controlled Text Dataset and Benchmark fo...") and Modal's ("GitHub - TheFloatingString/sam3-on-modal: Running SAM-3 infe...") could shift this matchup.

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Why Compare Fast.ai vs Modal?

Neck-and-Neck Battle

Just 2 ranks apart (#117 vs #119), this is one of the closest matchups in AI. Every product launch, research paper, and community sentiment shift could tip the balance.

Who Compares Fast.ai and Modal

Tech Decision Makers

Evaluating which platform offers better ROI and developer experience for enterprise adoption.

"Choose Fast.ai for proven scale, or Modal for potential agility advantage."

Developers & Builders

Choosing AI tools and platforms based on community sentiment, documentation quality, and ecosystem.

"Consider community feedback and integration ecosystem when making your choice."

Key Differences Between Fast.ai and Modal

  • **Community Perception**: Modal has notably stronger positive sentiment (30% higher).

Choosing Between Fast.ai and Modal

Consider Fast.ai if you value:

  • • Proven market leadership (#117)

Consider Modal if you value:

  • • Higher development activity
  • • Stronger community sentiment
  • • Higher substance-to-hype ratio

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