NVIDIA (NVDA): FY27 Q1 earnings call, May 20, 2026
On its May 20, 2026 earnings call (FY27 Q1), NVIDIA said 15 of the 43 words Kalshi and Polymarket listed; Parrot’s count agreed with all 43 settlements. Quotes below are at most 25 words each, with timed clips.
UpdatedMarkets
43 words · 15 settled yes · our count agreed on 43 of 43- Kalshi: company speakers + operator
Kalshi - Polymarket: anyone
Polymarket
backtest The probabilities on settled rows are a walk-forward backtest: the model as of before each event, computed after Parrot went live; they were not published at the time.
| Word | Result | Our count | All speakers | Agrees | Probability | Clip | Market |
|---|---|---|---|---|---|---|---|
| AI 30+ times | Yes | 104 | 104 | ✓ | 85%transcripts from the transcript model | Hear it 2:47, AI 30+ times | – |
| Agent / Agentic 10+ times | Yes | 26 | 26 | ✓ | 68%transcripts from the transcript model | Hear it 5:23, Agent / Agentic 10+ times | – |
| Data Center 20+ times | Yes | 24 | 24 | ✓ | 59%transcripts from the transcript model | Hear it 3:16, Data Center 20+ times | – |
| Vara / Rubin 10+ times | Yes | 23 | 23 | ✓ | 50%transcripts from the transcript model | Hear it 10:23, Vara / Rubin 10+ times | – |
| Token 20+ times | Yes | 22 | 22 | ✓ | 34%transcripts from the transcript model | Hear it 3:52, Token 20+ times | – |
| Blackwell 10+ times | Yes | 20 | 20 | ✓ | 80%transcripts from the transcript model | Hear it 2:40, Blackwell 10+ times | – |
| Anthropic | Yes | 9 | 9 | ✓ | 84%transcripts from the transcript model | Hear it 9:03, Anthropic | – |
| Hyperscaler | Yes | 8 | 11 | ✓ | 86%n=2+tx from settlement history blended with transcripts | Hear it 2:45, Hyperscaler | – |
| OpenAI | Yes | 7 | 7 | ✓ | 90%transcripts from the transcript model | Hear it 9:04, OpenAI | – |
| Incredible / Unprecedented | Yes | 5 | 5 | ✓ | 90%transcripts from the transcript model | Hear it 7:09, Incredible / Unprecedented | – |
| Meta | Yes | 2 | 2 | ✓ | 86%transcripts from the transcript model | Hear it 11:12, Meta | – |
| Self Driving | Yes | 2 | 2 | ✓ | 78%n=2+tx from settlement history blended with transcripts | Hear it 23:18, Self Driving | – |
| Silicon / Semiconductor | Yes | 2 | 2 | ✓ | 67%transcripts from the transcript model | Hear it 54:55, Silicon / Semiconductor | – |
| Gaming | Yes | 1 | 1 | ✓ | 90%n=3+tx from settlement history blended with transcripts | Hear it 5:27, Gaming | – |
| Humanoid | Yes | 1 | 1 | ✓ | 35%n=2+tx from settlement history blended with transcripts | Hear it 16:05, Humanoid | – |
| Omniverse | No | 0 | 0 | ✓ | 88%n=4+tx from settlement history blended with transcripts | – | |
| Gigawatt | No | 0 | 0 | ✓ | 86%transcripts from the transcript model | – | |
| Open Source | No | 0 | 0 | ✓ | 80%transcripts from the transcript model | – | |
| H20 | No | 0 | 0 | ✓ | 75%n=2+tx from settlement history blended with transcripts | – | |
| Cosmos | No | 0 | 0 | ✓ | 72%n=3+tx from settlement history blended with transcripts | – | |
| Gigascale | No | 0 | 0 | ✓ | 56%transcripts from the transcript model | – | |
| Superintelligence | No | 0 | 0 | ✓ | 56%transcripts from the transcript model | – | |
| TSMC | No | 0 | 0 | ✓ | 54%n=2+tx from settlement history blended with transcripts | – | |
| Talent | No | 0 | 0 | ✓ | 51%n=2+tx from settlement history blended with transcripts | – | |
| EU / Europe | No | 0 | 0 | ✓ | 49%transcripts from the transcript model | – | |
| GPU In Space / GPUs in Space | No | 0 | 0 | ✓ | 41%transcripts from the transcript model | – | |
| Automation | No | 0 | 0 | ✓ | 32%n=2+tx from settlement history blended with transcripts | – | |
| Trump | No | 0 | 0 | ✓ | 29%n=3+tx from settlement history blended with transcripts | – | |
| Taiwan | No | 0 | 0 | ✓ | 29%n=3+tx from settlement history blended with transcripts | – | |
| Bubble | No | 0 | 0 | ✓ | 28%transcripts from the transcript model | – | |
| Disney | No | 0 | 0 | ✓ | 28%transcripts from the transcript model | – | |
| Arizona | No | 0 | 0 | ✓ | 23%n=2+tx from settlement history blended with transcripts | – | |
| AGI | No | 0 | 0 | ✓ | 22%transcripts from the transcript model | – | |
| Domestic | No | 0 | 0 | ✓ | 21%n=2+tx from settlement history blended with transcripts | – | |
| Tariff | No | 0 | 0 | ✓ | 21%n=2+tx from settlement history blended with transcripts | – | |
| GM / General Motors | No | 0 | 0 | ✓ | 19%n=2+tx from settlement history blended with transcripts | – | |
| AMD | No | 0 | 0 | ✓ | 18%n=1+tx from settlement history blended with transcripts | – | |
| Circular | No | 0 | 0 | ✓ | 17%transcripts from the transcript model | – | |
| Ethereum | No | 0 | 0 | ✓ | 17%transcripts from the transcript model | – | |
| Layoff | No | 0 | 0 | ✓ | 17%transcripts from the transcript model | – | |
| Nanometer | No | 0 | 0 | ✓ | 17%transcripts from the transcript model | – | |
| TPU | No | 0 | 0 | ✓ | 17%transcripts from the transcript model | – | |
| VR / Virtual Reality | No | 0 | 0 | ✓ | 11%n=2+tx from settlement history blended with transcripts | – |
Market prices are mid quotes from Kalshi and Polymarket, shown for context, may be delayed by several minutes and are not a signal. Quotes as of Oct 21, 2026 04:22 UTC.
Transcript
quotes of at most 25 wordsSpeaker-labelled transcript · Source and credits · Used to count words; quotes of at most 25 words.
22 matches for “Token”; 5 quoted, at least 25 words apart.
…Grace Blackwell is the fastest training system as well as the lowest token generation cost at inference. Spectrum-X, our end-to-end Ethernet platform purpose-built for AI,…
…vast ecosystem and installed base, breadth of CUDA-accelerated application, and the lowest token cost provider. We are well-positioned to address a market opportunity that far…
…must choose the right architecture. With our extreme co-design approach, we deliver the industry's lowest token cost, the highest token throughput, and the highest ROI.
…2.7x increase in throughput and a 60% reduction in the cost per token on GB300 compared to just six months ago. NVIDIA Compute is not…
…GPU, it is the lifetime cost of an AI factory producing intelligence, token per watt, tokens per dollar, uptime, utilization, time to production, software durability,…
Where the listed words were said
…across our diverse end customer base, from hyperscalers to model makers to AI cloud providers and sovereign customers. In Q1, we also allocated capital effectively…
…and AI factories across industries and countries. Edge Computing highlights devices for agentic and physical AI, including PCs, gaming consoles, workstations, AI RAN based stations,…
This is critical to the market's development and our long-term position. Data center revenue of $75 billion was up 92% year-over-year and 21% sequentially, driven…
…Starting this year, AWS will add more than 1 million Blackwell and Rubin GPUs and are collaborating on Spectrum-X networking. At Google, Blackwell will be…
…we will make investments necessary to deliver the industry's lowest cost per token and the highest token throughput, which will help our customers and partners…
…reach $3 trillion-$4 trillion annually by the end of this decade. Our Blackwell architecture is everywhere, adopted and deployed by every major hyperscaler, every cloud…
…chips, infrastructure, models, and applications. Growth in the model layer, particularly at Anthropic and OpenAI, has been incredible, with momentum continuing to accelerate, including breakout…
…in each one of them. The easiest go-to-market, of course, is the hyperscaler, because there are only five or six of them. The rest of…
…Azure, CoreWeave, SpaceXAI, and more. Now, with the addition of Anthropic, too, OpenAI, Gemini, SpaceXAI, Meta, MSL, Microsoft AI, TML, Reflection, Perplexity, Cursor, and other…
…continuing to work vigorously on our supply chain ecosystem to address the incredible demand we see ahead of us, giving us full confidence in the…
…model. With the addition of Anthropic to our existing partners, OpenAI, xAI, Meta and Mistral AI, Gemini and many others, our share of frontier AI…
…centers and the edge. Edge including, of course, what most people see, self-driving cars, robotics, but a large growing network of computers inside manufacturing plants,…
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