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.
17 matches for “Inference”; 5 quoted, at least 25 words apart.
…revenue increase was also a record. We capitalized on the inflection in inference demand by ramping Blackwell systems across our diverse end customer base, from…
…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, is now larger than…
…the advent of ChatGPT, we have witnessed mainstream AI transition from one-shot inference to reasoning and to now agentic. AI is no longer a nice-to-have.…
MLPerf inference results are in. Once again, we swept every benchmark as Blackwell Ultra delivered the highest throughput across the broad set of models and…
…across five accelerated racks, Vera Rubin will deliver up to 35x higher inference throughput and up to 10x greater AI factory revenue compared with Blackwell.…
Where the listed words were said
…Data Center, we will report two sub-markets, Hyperscale and ACIE, which incorporates AI clouds, industrial, and enterprise. Hyperscale will include revenue from the public cloud…
…analysts now forecasting hyperscale CapEx to exceed $1 trillion in 2027 and agentic AI beginning to proliferate all industries, AI infrastructure spending is on track…
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…
…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…
Robust Blackwell workstation demand was a strong contributor to the growth, while consumer demand fell modestly due to higher memory and system prices. Our physical…
…through AWS, Azure, CoreWeave, SpaceXAI, and more. Now, with the addition of Anthropic, too, OpenAI, Gemini, SpaceXAI, Meta, MSL, Microsoft AI, TML, Reflection, Perplexity, Cursor,…
…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…
…reason why we heard about the frontier AI companies, both Anthropic and OpenAI, growing at an incredible pace. The fact that they can grow within…
…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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