Superintelligence Plots

DeepSeek’s second private financing closed at about $15 billion with a reported valuation of roughly $74 billion going into the final close, after a June round that raised about $7.4 billion at a Caixin-reported post-money valuation of about $52 billion. A second, independent SI Plots dataset already showed DeepSeek’s reported private valuation rising sharply across 2026 toward about $74–75 billion (DeepSeek’s reported private valuation climbed about sevenfold in 2026); this chart adds the capital raised in each round and uses the Caixin post-money figure for June rather than other reported June marks. That paired raise-and-valuation path is the quantitative core of the SI News report that DeepSeek nearly doubled its fundraising target amid strong investor demand ahead of a possible Shanghai listing.

Sources & Notes

• Original story: DeepSeek Raises $15B Ahead of Shanghai IPO | OpenAI Opens Decisions API to All Customers | Kuaishou Launches Kling 4.0 Video Model
• Data sources: PYMNTS (2026). DeepSeek Raises $15 Billion Ahead of Planned Shanghai IPO; Quartz (2026). DeepSeek raised about $15 billion ahead of a possible IPO; Caixin Global (2026). DeepSeek Reaches $52 Billion Valuation in Round Backed by Tencent, CATL; Reuters (2026). DeepSeek slated to raise $7 billion in maiden funding round, sources say
• Other references: CNBC (2026). DeepSeek considers doubling latest funding round to up to $15 billion, sources say
• Notes: June 2026 Round 1 capital raised (~$7.4B) and post-money valuation (~$52B / >350B yuan) from Caixin Global and Reuters reporting. October 2026 Round 2 capital raised (~$15B / ~100B yuan) and pre-close valuation (~$74B) from The Wall Street Journal as reported by PYMNTS and Quartz (2026-10-22). The chart plots Round 1 valuation as post-money and Round 2 valuation as the reported pre-money figure into final close; amounts are from people familiar with the matter and are not a company filing. Observation window: reported closes on or about 2026-06-16 and 2026-10-22. Access date: 2026-10-23.

Meta’s capital expenditures, including finance-lease principal, reached $34.9 billion in the third quarter of 2026, about 4.9 times the $7.1 billion it spent in the first quarter of 2023, while quarterly free cash flow fell from $12.4 billion in the first quarter of 2026 to negative $2.1 billion, its first negative quarter in this series. In other words, Meta’s AI data-center buildout now costs more than all the cash its operations generate, even though third-quarter revenue rose 26% year over year to $64.6 billion. That context matters for the SI News report that Meta raised the floor of its 2026 capex outlook to $135 billion and approved a new share class to help fund the expansion.

Sources & Notes

• Original story: Anthropic Launches Proactive Claude Duet Agent | Meta Raises AI Capex as Muse Passes 10M | Chinese AI Tool Traced in Japan Hacking Spree
• Data sources: Meta Platforms, Inc (2026). Meta Reports Third Quarter 2026 Results; Meta Platforms, Inc (2026). Meta Reports Second Quarter 2026 Results; Meta Platforms, Inc (2026). Meta Reports First Quarter 2026 Results; Meta Platforms, Inc (2026). Meta Reports Fourth Quarter and Full Year 2025 Results; Meta Platforms, Inc (2025). Meta Reports Third Quarter 2025 Results; Meta Platforms, Inc (2025). Meta Reports Second Quarter 2025 Results; Meta Platforms, Inc (2025). Meta Reports First Quarter 2025 Results; Meta Platforms, Inc (2025). Meta Reports Fourth Quarter and Full Year 2024 Results; Meta Platforms, Inc (2024). Meta Reports Third Quarter 2024 Results; Meta Platforms, Inc (2024). Meta Reports Second Quarter 2024 Results; Meta Platforms, Inc (2024). Meta Reports First Quarter 2024 Results; Meta Platforms, Inc (2024). Meta Reports Fourth Quarter and Full Year 2023 Results; Initiates Quarterly Dividend; Meta Platforms, Inc (2023). Meta Reports Third Quarter 2023 Results; Meta Platforms, Inc (2023). Meta Reports Second Quarter 2023 Results; Meta Platforms, Inc (2023). Meta Reports First Quarter 2023 Results
• Notes: Quarterly figures for Q1 2023 through Q3 2026 in nominal USD billions, rounded to one decimal, as reported in Meta’s earnings press releases (accessed 2026-10-23); points are plotted at each quarter’s end date. Capital expenditures include principal payments on finance leases. Free cash flow is Meta’s non-GAAP measure: cash from operating activities minus purchases of property and equipment and principal payments on finance leases. Meta’s outlook for full-year 2026 capital expenditures is $135-145 billion.

Anthropic’s booked revenue has tracked the run-rate figures it publicized: it booked $4.6 billion in 2025 against a stated run rate of about $5 billion in August 2025, and $16.8 billion in Q3 2026 (about $67 billion annualized) against the $65 billion run rate reported for the end of July. That matters because a run rate is a company-chosen projection, and the booked quarters show the roughly 65-fold climb from about $1 billion in early 2025 was realized revenue, even as quarter-on-quarter growth slowed from 147% in Q2 to 45% in Q3. The same booked figures underpin the draft IPO prospectus covered in the SI News roundup, which pairs $16.3 billion of first-half revenue with an $80.7 billion net loss.

Sources & Notes

• Original story: OpenAI Models Come to Google Cloud | Anthropic Draft S-1 Shows $80.7B Loss | Mistral Launches Voxtral 3 Voice Stack
• Data sources: Anthropic (2025). Anthropic raises $13B Series F at $183B post-money valuation; Reuters (2025). US tech startup Anthropic unveils cheaper model to widen AI’s appeal; Anthropic (2026). Anthropic raises $30 billion in Series G funding at $380 billion post-money valuation; Anthropic (2026). Anthropic expands partnership with Google and Broadcom for multiple gigawatts of next-generation compute; Anthropic (2026). Anthropic raises $65B in Series H funding at $965B post-money valuation; Capoot, A., & Rooney, K (2026). Anthropic tells investors annualized revenue run rate climbed to $65 billion in July; Vinn, M., & Hu, K (2026). At Anthropic pre-IPO meet: ‘Thinking’ caps, surging revenue, no human extinction
• Other references: Al Jazeera Staff and Reuters (2026). Anthropic posts $80bn loss in first half of 2026: WSJ
• Notes: Stated run rate is Anthropic’s annualized revenue (latest month times 12) as stated by the company or, for 2025-10 and 2026-07, by a company spokesperson or investor update reported by Reuters and CNBC; it is plotted at its as-of date, with month-only statements (beginning of 2025, by August 2025, earlier in May 2026) placed on the first of that month. Booked revenue, annualized, is full-year 2025 revenue (nearly $4.6 billion, plotted at mid-year) and quarterly 2026 revenue of $4.7, $11.6 and $16.8 billion multiplied by 4 (plotted at each quarter’s midpoint); the quarterly figures come from investor-day attendees via Reuters and are unaudited, though Q1 plus Q2 equals the $16.3 billion first-half figure in the draft prospectus. The y-axis is logarithmic; figures are nominal USD and were accessed 2026-10-22.

In an independent test run on 2026-10-20/21 over public APIs, Inception’s diffusion model Mercury 3 decoded long (~8k-token) answers at a median 849–893 visible tokens per second, 2.6–2.8x Claude Haiku 5.5 with thinking off (324 tok/s) and 6.4–6.8x GPT-6 Luna with reasoning off (132 tok/s), while scoring 80.6–86.0% pass@1 on 637 coding problems, level with those two models (86.1% and 83.2%) rather than ahead of them. The measured rate sits below Inception’s 1,068 tok/s launch figure (the tester rates the claim “close”, since client-side timing includes network overhead; OpenRouter separately lists a 247 tok/s median throughput for Mercury 3’s live traffic, a different all-traffic measure), and an ordinary autoregressive model, gpt-oss-120b served on Cerebras hardware, decoded 2,396 tok/s at 82.4%, so diffusion is one route to speed rather than the only one. That answers the “if the benchmarks hold up” caveat in today’s SI News item on Mercury 3: the speed lead over the big labs’ fast models is real but a constant factor, and code quality roughly matches them instead of beating them.

Sources: Bruce Li, “Mercury 3 vs. the Fast Autoregressive Models: A Technical Report” (2026-10-21), §5.1 table (pass@1, run r2-uc1-main-20261021T034053Z) and §5.4 table (long-answer visible decode speed, run r3-uc1-length-20261021T152238Z) · study code and configs (GitHub) · Inception, “Diffusion at Scale: Introducing Mercury 3” (1,068 tok/s claim) · OpenRouter, Mercury 3 model page (live P50 throughput, viewed 2026-10-21)
Original story: SI News: DeepSeek Open-Sources Its DeepInfer Inference Engine | US Bans DeepSeek From Civilian Agencies | Inception Launches Mercury 3 Diffusion Model
Notes: One point per model setting. Speed is the median visible decode rate (visible tokens after the first visible token, measured client-side from one US West host) on ~8,000-token answers, at each model’s lowest setting; Mercury 3 “low” includes hidden reasoning before its first visible token. Accuracy is pass@1 across 164 HumanEval+, 378 MBPP+ and 95 LiveCodeBench v6 problems, 5 samples each. Both runs come from the same single-author study; they compare products (model plus serving stack), not architectures. The x axis is logarithmic.

MiniMax’s M3.1 Flash (released 2026-10-19) scores 42.7 on the Artificial Analysis Intelligence Index at a measured $0.22 per index task. That puts it close to far pricier rivals — Qwen3.8 Max scores 45.4 at $5.41 per task, about 25 times the cost — in a plot of 20 frontier models from Artificial Analysis’s live leaderboard.

Source: SI News article

Data: Artificial Analysis