Google strikes back, Databricks’ premium, and falling AI lab revenue multiples

Google released Gemini 3.7 Flash, a new AI model priced at $1.50/$7.50 per million input/output tokens, which appears competitive with Claude Sonnet 5 and is offered at a 50% discount on OpenRouter. OpenAI introduced an 'Ultrafast' mode for GPT-5.6 Sol that makes the model up to 14x faster, while Cerebras hinted its chip technology serves 5.6 Sol at 10x speed, underscoring speed as a key competitive vector in AI.

Google strikes back, Databricks’ premium, and falling AI lab revenue multiples Today we cover Google's new model, ponder why Databricks has leverage over its investors, and ask if OpenAI and Anthropic are big enough for their britches. Welcome to . Cautious Optimism https://www.cautiousoptimism.news/ , a newsletter on tech, business, and power. Modestly upbeat Friday. I’m heading out on a poker trip shortly, so today’s newsletter will be slightly tömör . संक्षिप्त, if you will. To work — Alex 📈 Trending Up: Valuation haircuts https://www.afr.com/technology/canva-investors-wipe-10b-from-valuation-20260813-p60o48 … data center PR http://www.cnn.com/2026/08/11/business/data-centers-ai-economy … a return to the steam-era https://x.com/dave brown24/status/2088001399313551703 … my lack of shock https://www.wsj.com/business/earnings/applied-materials-posts-higher-profit-revenue-on-continued-ai-demand-45c15ab4 … Nubank, after earnings https://finance.yahoo.com/markets/stocks/articles/nu-holdings-shares-surge-first-101818296.html … Apple, the Chinese AI lab https://www.reuters.com/business/retail-consumer/apple-trains-its-own-ai-model-china-market-with-alibabas-support-sources-say-2026-08-14/ … consumer spending https://www.census.gov/retail/marts/www/marts current.pdf 📉 https://finance.yahoo.com/news/servicenow-pledges-1-5bn-investment-110000403.html Trending Down: Legal gambling https://www.atg.wa.gov/news/news-releases/judge-orders-kalshi-cease-numerous-washington-operations … legal gambling https://www.ft.com/content/4e3774b6-52e5-4b8a-be76-0bb87495e1f0 … Japan-Russia relations https://www.cnbc.com/2026/08/14/putin-kuril-islands-japan.html … JD.com, after earnings https://www.retail-insight-network.com/news/jd-com-returns-to-operating-profit/ … personal privacy https://x.com/AriX/status/2087996577227124775 … Chinese drones in America https://www.whitehouse.gov/fact-sheets/2026/08/fact-sheet-president-donald-j-trump-bolsters-national-security-and-strengthens-u-s-supply-chains-by-imposing-tariffs-on-drones-and-their-parts-and-components/ The Rundown Google makes a return: Around the same time our take on how Google had dropped the ball went live yesterday https://www.cautiousoptimism.news/google-squandered-its-ai-lead/ , the company released a new AI model https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-3-7-flash/ . Talk about timing. The new Gemini 3.7 Flash appears competitive with Claude Sonnet 5 at a price post-discount of $1.50/$7.50 per million input/output tokens. Despite the oft-discussed delays in releasing its next ‘Pro’ model, demand for Google’s models has remained quite stable https://openrouter.ai/google , per some third-party metrics. And OpenRouter is offering 3.7 Flash for 50% of its introductory price, similar to the discounts the model router offered for OpenAI’s GPT-5.6 Luna and Terra models. Goddamn, I love competition. Model speed is becoming a critical vector: For my uses, current SOTA AI models at high reasoning levels provide all the capability I can use, at a cost thank you, subscription pricing that feels more than fair. But I’ve found that I could use more speed, and others online seem to agree. AI labs have listened. Not only are Gemini 3.7 Flash and Nvidia’s recent Nemotron 3.5 Lightning the fastest small models on the market, per AA https://artificialanalysis.ai/ speed , but OpenAI has announced a new ‘ Ultrafast https://openai.com/index/previewing-ultrafast/ ‘ mode for GPT-5.6 Sol that makes the model up to 14x faster than its standard setting. - Notably, Cerebras hinted https://finance.yahoo.com/quote/CBRS/earnings/CBRS-Q2-2026-earnings call-686677.html at the new Ultrafast mode in its earnings call, telling investors that its chip technology “serves 5.6 Sol at a speed that is 10X faster” than other providers, and that “fast tokens are in demand and command a premium at market.” The Ultrafast mode will deliver Sol at up to 750 tokens per second, about twice the speed of Gemini 3.7 Flash, albeit at an unlisted price. Expect to pay through the nose, and for tokens/second to become as critical a metric as token efficiency and raw token costs. Chinese weights are coming with a price tag: At launch, Kimi K3 https://www.cautiousoptimism.news/china-finally-built-an-american-ai-model/ wasn’t accompanied by its weights, and when Moonshot did release the data, it added a clause https://www.cautiousoptimism.news/moonshot-opens-the-open-model-tollbooth/ that if you wanted to serve the model commercially, you had to remit a portion of the revenue back to the company. Alibaba Qwen 3.8 Max , and MiniMax M3 have taken similar steps. Today, Z.ai announced GLM-5.3 https://z.ai/blog/glm-5.3 , which improves on GLM-5.2 with more post-training. The new model is better, naturally, but comes with a caveat: “The model weights of GLM-5.3 will be publicly available soon in two weeks.” I wouldn’t be shocked to see Z.ai also dropping the model weights along with a requirement to share revenue on sales of third-party inference. As discussed, the Chinese AI’s free lunch era is coming to a close https://www.cautiousoptimism.news/the-end-of-chinese-ais-free-lunch-era/ . - Why? Because Chinese AI labs want to raise huge private rounds and/or go public. That means they need to get their customers’ noses closer to the market grindstone. So, higher rates and required commercial prices are the theme of the quarter. Databricks: As expected, Databricks has raised yet more funding https://www.databricks.com/company/newsroom/press-releases/databricks-grows-80-yoy-surpasses-7b-revenue-run-rate-scales . This round $5 billion at a $190 billion valuation was pipped to allow the data and AI giant to buy more GPUs, but now that Databricks is quasi-public, it was kind enough to provide us with the startup equivalent of an earnings report: - Databricks’ revenue rose more than 80% in the last year, and total run-rate revenue crossed $7 billion. - The company maintained its adjusted free cash flow generation on a trailing-twelve-month basis. - It also saw surging demand for its Lakehouse $1.5+ billion run rate, 100% growth rate and Lakebase $100 million run rate products. While the foundation model labs were busy hogging the headlines, Databricks has taken advantage of the rising demand for data usage in the AI era. The company may never go public, but we can still cheer it on from the sidelines. Are OpenAI and Anthropic big enough for their britches? OpenAI and Anthropic sometimes bend to sharing a nibble or two of their financial performance whenever they raise money, and promptly shut up afterwards. But with their IPOs looming, some information is leaking out: The FT, discussing Anthropic https://www.ft.com/content/840ac156-af1c-4a82-b260-ae791072fcfa?syn-25a6b1a6=1 : “Investors expect the Claude maker’s annualised revenue to be between $100bn and $120bn by the end of 2026 — using the start-up’s preferred measure, which infers full-year sales from recent performance — up by more than 10 times over the course of 2026.” Bloomberg, discussing OpenAI https://www.bloomberg.com/news/articles/2026-08-13/openai-s-revenue-run-rate-tops-40-billion-ahead-of-ipo : “OpenAI is on track to generate annualized revenue of more than $40 billion based on its current performance, according to people familiar with the matter, roughly doubling its run rate from the end of 2025 and bolstering the company’s plans for a Wall Street debut.” Let’s compare that to Databricks, which with its new $190 billion price tag, is valued at 27x its current run-rate revenues. OpenAI, at the newly reported revenue run-rate of $40 billion and its last disclosed valuation of about $852 billion, would be valued at 21.3x its run rate. Meanwhile, Anthropic would be valued at 9.7x to 8.0x its run-rate revenues of $100 billion to $120 billion, given its current $965 billion price tag. Those multiples are precisely why Anthropic’s backers think it could fetch a valuation north of $1 trillion, even as much as $2 trillion, when it eventually goes public. OpenAI appears well positioned to defend its current valuation, though it’s critical to keep in mind that trailing GAAP revenues will be much smaller than the run-rate numbers we’re discussing. In the case of Anthropic, the market is curious how the company accounts for partner revenue costs. Regardless, OpenAI and Anthropic are together probably clocking run-rate over $100 billion today. Against an aggregate valuation present-day of ~$1.82 trillion, they don’t seem absurdly expensive. - So why does Databricks have a higher revenue multiple than the leading AI labs? First, it’s entirely de-risked: Accelerating growth paired with years of positive free cash flow make for a hugely valuable company. - Also, given that the company has had lower capital needs thanks to its business model and cash generation, it has more leverage over investors than the cash-hungry labs do today. That reading feels accurate given their recent momentum. OpenAI’s Codex is growing like a weed https://x.com/thsottiaux/status/2087706104814023111 , and the company’s overall run-rate revenue grew 20% in July https://x.com/steph palazzolo/status/2087944243406921937 , while enterprise revenue grew 32% in a month . Bring on the IPOs. So long as their cash burn goes down, the AI labs have done the hard work to grow into their valuations. Hell yeah.