>Fast.ai vs Thinking Machines Lab
Fast.ai AI Company Profile & Rankings • Thinking Machines Lab 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.
Thinking Machines Lab
Thinking Machines Lab Inc. is an American artificial intelligence startup and public benefit corporation based in San Francisco. Founded in February 2025 by former OpenAI chief technology officer Mira Murati, the company develops AI technology and infrastructure. In July 2025, it completed a $2 billion early-stage funding round led by Andreessen Horowitz, achieving a $12 billion valuation with investments from Nvidia, AMD, Cisco, and Jane Street. The company launched Tinker, an API for fine-tuning open-weight language models on its internal infrastructure, in October 2025. Thinking Machines Lab's initial team included several high-profile researchers from OpenAI, Meta AI, and Mistral AI, though it has subsequently experienced significant executive departures back to competitors.
Fast.ai versus Thinking Machines Lab: Live 2026 Comparison
Based on real-time data, Thinking Machines Lab outperforms Fast.ai across both activity (4 vs 0 events this week) and community sentiment (65% vs 30%). This comparison draws on 4 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 Thinking Machines Lab has more authentic positioning (gap: 7.6) compared to Fast.ai (10.0). Data refreshes every 5 minutes. Compare other AI companies →
Fast.ai vs Thinking Machines Lab: Key Signals
Data refreshes every 5 minutes. Compare other companies →
Fast.ai vs Thinking Machines Lab: Head-to-Head
| Metric | Fast.ai | Thinking Machines Lab |
|---|---|---|
| Rank | #117 | #61 |
| Overall Score | 8.5 | 17.6 |
| 7-Day Events | 0 | 4 |
| 30-Day Events | 0 | 4 |
| Sentiment | 30% | 65% |
| Momentum 7d vs 30d velocity | 0% | +430% |
| Hype Score | 10.0 | 7.6 |
| Reality Score | 0.0 | 0.0 |
| Hype Gap | +10.0 | +7.6 |
📊 Visual Comparison
Compare 5 key metrics on a 0-100 scale. Larger area = stronger overall performance.
Metric Definitions:
What Separates Fast.ai from Thinking Machines Lab
Who Ships Faster: Thinking Machines Lab or Fast.ai?
Thinking Machines Lab logged 4 events this week vs Fast.ai's 0 — a significant difference in product launches, research papers, and code commits.
What Users Think of Thinking Machines Lab vs Fast.ai
Thinking Machines Lab has 65% positive sentiment vs Fast.ai's 30%. That 35-point gap is significant — it signals stronger user satisfaction and fewer community complaints about Thinking Machines Lab.
Does Thinking Machines Lab Deliver on Its Promises?
Thinking Machines Lab's hype gap of 7.6 vs Fast.ai's 10.0 means Thinking Machines Lab has mostly honest positioning, while its competitor shows more marketing inflation.
Where Thinking Machines Lab and Fast.ai Rank
Thinking Machines Lab at #61 outranks Fast.ai at #117 among 2,800+ AI companies. The 56-rank gap reflects different market tiers and adoption levels.
Fast.ai vs Thinking Machines Lab: Momentum Trend
Thinking Machines Lab is accelerating (430% velocity growth) while Fast.ai is flat — a diverging trend worth watching.
Latest Signals: Fast.ai vs Thinking Machines Lab
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 HotFine-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
Thinking Machines Lab(4 events this week)
Thinking Machines Lab: $120M Valuation Per Employee and the Nvidia Gigawatt Deal
• Dev.to Machine Learning TagMira Murati’s Thinking Machines strikes multibillion chip deal with Nvidia - Financial Times
• Google News - AI GeneralThe New AI Moat: Why Compute Access Is Now More Important Than Talent
• Dev.to AI TagNVIDIA GTC 2026: Live Updates on What’s Next in AI
• NVIDIA AI BlogNvidia makes 'significant investment' in Mira Murati's Thinking Machines Lab
• CNBC Technology
Analysis: Fast.ai vs Thinking Machines Lab
Thinking Machines Lab (#61) leads Fast.ai (#117) by 56 ranks, reflecting a meaningful difference in overall market position and activity.
Thinking Machines Lab is gaining momentum (430% velocity increase) while Fast.ai is holding steady, signaling potential change in this matchup.
Community sentiment diverges sharply: Thinking Machines Lab at 65% positive vs Fast.ai's 30%. Thinking Machines Lab maintains more authentic positioning with a hype gap of 7.6, 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 Thinking Machines Lab's ("Thinking Machines Lab: $120M Valuation Per Employee and the ...") could shift this matchup.
Want More Details?
View full company profiles with event history and trend analysis
Why Compare Fast.ai vs Thinking Machines Lab?
Cross-Tier Comparison
Comparing Thinking Machines Lab (#61) with Fast.ai (#117) reveals the 56-rank gap between different market tiers. Useful for understanding what separates top-tier from emerging players.
Who Compares Fast.ai and Thinking Machines Lab
Enterprise Buyers
Comparing market leader against emerging alternative to balance stability vs innovation.
"Thinking Machines Lab for enterprise-grade reliability, Fast.ai for cutting-edge features."
Key Differences Between Fast.ai and Thinking Machines Lab
- **Community Perception**: Thinking Machines Lab has notably stronger positive sentiment (35% higher).
Choosing Between Fast.ai and Thinking Machines Lab
Consider Fast.ai if you value:
Consider Thinking Machines Lab if you value:
- • Proven market leadership (#61)
- • Higher development activity
- • Stronger community sentiment
Create Your Own Comparison
Compare any two AI companies from our database of 100+ tracked companies. Get instant access to real-time metrics, activity data, and marketing honesty scores.