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A few takeaways on ChatGPT advertising and what it means for Meta, based on FUNDA’s latest META preview and checks with 6 ad agencies: 1/ ChatGPT ads are growing quickly, but scale and budget impact are two different questions. According to the report, ChatGPT’s ad revenue run-rate reached $1bn by August 31, following the start of testing in February. Ads were live in more than 60 countries by September 23. The agency checks show adoption is rising, though from a small base: A. North America Agency A: ~55–58 advertisers are testing ChatGPT ads, but only ~7–8 have moved into regular budgets. ChatGPT still represents less than 1% of the total digital ad budget the agency tracks. B. Asia Agency A: ChatGPT spend rose from ~1/60 of Google spend in 2Q to ~1/10 in 3Q. The agency expects ~1/8–1/7 in 4Q. C. Asia Agency C: ~170 advertisers are running ChatGPT ads, but results have yet to meet expectations. The distinction is between advertisers trying the platform and advertisers committing recurring budgets. Adoption is moving faster than evidence of durable returns. 2/ For Meta, where the money comes from matters as much as how fast ChatGPT grows. The report describes two phases: A. Test budgets: These are generally fixed. Money allocated to ChatGPT can come out of spending that Meta, Google or another platform would otherwise receive. B. Regular budgets: Once ChatGPT becomes an ongoing line item, agencies say clients generally seek additional funding. That would reduce the direct pressure on existing platform budgets. Across the six agencies, Google has the most direct overlap. Traditional US advertisers tend to fund ChatGPT from search budgets, while smaller, more agile companies are more likely to treat it as additional spend. There is an exception worth highlighting: Asia Agency A reports funding coming from several platforms, including Meta. My read: the checks support limited visible impact on Meta so far, but they do not establish that all ChatGPT spending is incremental. The key question is how much test spending becomes recurring spend—and how that recurring spend gets funded. 3/ Performance is mixed, and measurement could change the picture. A. Some encouraging early results: North America Agency A reports good ROI, though volume is limited. The European agency sees ChatGPT working as a complement to search and retail media. B. Weak conversion in other accounts: Asia Agency A reports strong clicks but a sharp drop-off afterward. For one education client, cost per lead was ~1.8x Google’s and well above Meta’s. Asia Agency B reports poor returns and few repeat clients. C. Possible under-attribution: Asia Agency C suspects some users discover products on ChatGPT but convert later through Meta or another channel. This remains an agency hypothesis; better measurement could change how advertisers allocate budgets. FUNDA’s conclusion is that ChatGPT is beginning to affect the ad industry, with spending still mostly incremental or coming from Google. It does not include a ChatGPT drag in its Meta model. My takeaway: ChatGPT is becoming a credible destination for ad budgets, but the competitive impact remains early and uneven. For Meta, the most useful indicators are repeat spending, conversion performance and the source of funding—not advertiser adoption alone. Subscribe to FUNDA Institutional Solution to access more in-depth reports. [email protected].

How does FUNDA’s latest $META Preview analyze ChatGPT’s impact on the advertising industry?

Research|LLM: DeepSeek V4.1-Flash-1017 Reaches the Top Tier of Open-Weight Models, Still Behind Proprietary Frontrunners Faster, lower-cost coding and agent tasks intensify competition DeepSeek released V4.1-Flash-1017 on October 17, an update to the V4.1 Flash model launched on September 10. The API model name is unchanged. Pricing remains $0.30 per million input tokens and $1.20 per million output tokens, with a 50% off-peak discount. The weights are available under the MIT license. The new version outperforms its predecessor on all 11 benchmarks reported by DeepSeek: its Terminal-Bench 4.0 score increased from 31.2 to 42.3 and its DeepSWE score from 74.2 to 77.0. In our view, it now offers the best balance of capability and cost among open-weight models for coding and agent tasks. Since the release, some articles have claimed that 1017 beats GPT-6, mainly on the strength of its DeepSWE score and cost per task. Our preliminary view is that 1017 has joined Kimi K3 and Xiaomi’s MiMo-V2.6 Pro in the top tier of open-weight models. DeepSeek has made clear progress, but this update has not brought the open-weight frontier any closer to the leading proprietary models. Our channel checks indicate that data from the previous generation of proprietary models remains accessible. Distilling from newer models, particularly Fable 5.1 and Opus 5.5, has become more difficult. Opus 5.5 retains a clear lead, and 1017 has not narrowed the gap. OpenAI also has an even stronger internal model, Bel. Detailed Report fundaai.substack.com/p/deepl…

Financing conditions can affect both neoclouds’ cost of capital and their customers’ ability to pay. Neolabs have become important marginal buyers of short-term GPU capacity, paying high rental rates despite uncertain business models. As we flagged on a client call last month, we think their funding could support roughly six to twelve months of spending, after which continued purchases would depend on raising more capital. $CRWV $NBIS $IREN Read more in our weekly post: fundaai.substack.com/p/weekl…

Visibility in semis is several quarters at best. You could argue about $AMD attractiveness as a second source hedge with ASICs in the picture but debating forecasts out to 2030 is not very helpful (in our view).

Thanks @ParadisLabs. We drew some observations from our conversations with people working in the field and published them here: fundaai.substack.com/p/deepp…

In addition to OCP, we also attended the inaugural edition of the iconic Sohn conference in Tokyo. Some Funda readers recognised us and we made new friends. Get in touch with @illyquid for feedback on the following stock pitches: 🔵 Oasis Management - Aoki Holdings 🔵 Indus Capital Partners - Rigaku 🔵 Blue Orca Capital - Rohm / Chubu Electric / TRE Holdings / Toshiba / Kioxia 🔵 Ruane Cunniff - Money Forward 🔵 Pertento Partners - Long Hanwha Corp; Short Ecopro 🔵 SILQ Capital - Makino Milling 🔵 Japan Catalyst - OBIC Business Consultants 🔵 TriVista Capital - Harmonic Drive 🔵 CHANGE Global Investment - Telkom Indonesia 🔵 Polymer Capital - Orix @InvestInJapan @MomokaYokoyama_ @yasutaka_tamura

As we approach AGI, more compute has to go to training, which makes ROI harder to prove, which makes the investing experience less pleasant, as our collective experience this week showed. Read our reaction to the Anthropic ARR number here: fundaai.substack.com/p/colum… Thanks for the shoutout @SaaSletter !

$SMTC sounded confident about the next two years but conservatively guided growth in line with the industry in 2029 and 2030. More importantly, we came away impressed with the team's technical chops.

Column|Anthropic: What the New 3Q Numbers Mean Anthropic disclosed 3Q26 revenue of $16.8Bn during its just-completed pre-IPO investor day. The company had previously disclosed 2Q26 revenue of $11.5Bn and 1Q26 revenue of $4.7Bn. There is speculation that the company guided to $100Bn of ARR by year-end, but we don’t believe it has given explicit guidance. Based on the disclosures and our own tracking over time, we built a full-year ARR and revenue model for Anthropic. Detailed Report fundaai.substack.com/p/colum…

Review| $TSM 26Q3: Revenue Guidance Beats Expectations as Expansion Weighs on Margins TSMC expressed confidence in advanced-node and long-term AI demand during its earnings call. Management said that, alongside discussions with direct customers and their downstream customers, its teams had checked US data center construction and power availability, with encouraging feedback so far. Agentic AI and open-source models are also increasing demand for computing chips. TSMC is responding by adding N3 fabs, departing from its usual practice of stopping capacity additions once a node reaches its target. Detailed Report fundaai.substack.com/p/revie…

Review| $ASML 26Q3: Upgrades Lift Gross Margin; Capacity Expansion Awaits Further Clarity ASML’s Q3 gross margin and Q4 guidance both beat expectations. The company narrowed its 2026 revenue guidance to EUR 44–45b and raised its full-year gross margin guidance to around 56%, driven by continued strength in the upgrade business within Installed Base Management. The company stated that its plan to increase capacity by 30% in 2027, together with the further 30% increase in 2028 that had been under investigation, will still not fully meet customer demand, and it is now looking into expanding 2028 capacity beyond 30%. Customers have expressed interest in placing orders for 2029 and 2030, although ASML has not yet accepted those orders. We raise our 2026/27/28 EPS forecasts to EUR 42.5/61.4/76.9. Detailed Report fundaai.substack.com/p/revie…

$ORCL and $CRWV face a repricing of credit risk, along with SoftBank in Japan. Higher credit risk premiums → potentially higher costs on new financing → pressure on neoclouds’ purchasing power → a possible downgrade in AI hardware order growth. $ORCL: 5Y CDS widened 26bp overnight to a record 288bp. $CRWV: CDS broke through 1,000bp, and its 2032 bonds fell to 77 cents on the dollar. CDS on Amazon, Alphabet, Meta and NVIDIA also hit record highs, though their spreads remain well below Oracle’s. Our AI Capex Credit Watch: funda.ai/play/cds?ref=chat_c…