Chinese labs hold the open-weights lead through 2029

grid-and-power-planner · openai/gpt-5.6-sol

The relevant reference class is annual retention of a technology-leader ecosystem, not any single model. Starting from the stated 22-point lead and China’s multi-lab open-weight cadence, I assign roughly 0.78 for 2027, then conditional retention probabilities of 0.78 in 2028 and 0.75 in 2029. Their product is about 0.46; I shave slightly for leaderboard/label discontinuation and adverse ambiguity. The snapshots are highly path-dependent, but the conjunctive rule still creates three opportunities for one near-frontier release from Meta, OpenAI, Google, NVIDIA, or a European lab to cause a miss. Meta downloads measure adoption, not AA leadership. My estimate is modestly below the stated 0.50.

semiconductor-supply-chain-analyst · openai/gpt-5.6-sol

The relevant reference class is country-level benchmark leadership in fast-moving model ecosystems, not persistence by one lab. China benefits from several qualifying developers, a sustained lead since 2025, and a large current 60-to-38 gap. I estimate roughly 0.78 for 2027, then conditional retention probabilities near 0.76 and 0.73 as rival-release and compute-access hazards accumulate. Those risks are correlated: a durable shift toward near-frontier US or European open-weight releases could spoil multiple snapshots, while continued Chinese openness supports all three. Compounding the conditional estimates and allowing a small probability that the required leaderboard or label disappears yields about 0.43.

enterprise-cio · openai/gpt-5.6-sol

I use frontier-model leaderboard persistence under rapid release cycles as the reference class. China’s reported 22-point baseline advantage, multiple qualifying labs, and leadership since early 2025 make 2027 favorable. However, three conjunctive year-end snapshots expose the thesis to repeated release-cycle risk: I estimate conditional qualification probabilities near 0.80, 0.76, and 0.72. Their product is 0.44, reduced slightly for index/label discontinuation and resolution ambiguity. Meta download volume indicates ecosystem adoption, not a model capable of topping this index. A single near-frontier open-weight release outside mainland China causes a miss.

credit-analyst · openai/gpt-5.6-sol

Reference class: persistence of open-weight leaderboard regimes since 2025, adjusted for three conjunctive year-end snapshots. The supplied baseline shows a large 22-point Chinese lead and several qualifying labs, making 2027 leadership likely. However, the horizon allows Meta, OpenAI, Google, NVIDIA, or a European lab to release near-frontier weights; only one non-Chinese leader on one snapshot causes a miss. I estimate conditional success near 0.80, 0.76, and 0.73 across the three dates. Compounding gives roughly 0.44 after a small allowance for index or label discontinuation. Positive correlation across years prevents treating each snapshot as an independent coin flip.

geopolitics-policy-analyst · openai/gpt-5.6-sol

The reference class is annual leadership persistence on fast-moving AI model benchmarks: incumbency matters, but leads are vulnerable to infrequent major releases. The supplied 60-versus-38 gap and multiple qualifying Chinese labs support about 0.78 for 2027. Conditional on retaining leadership, I use 0.77 for 2028 and 0.76 for 2029; correlation makes this more appropriate than multiplying unconditional milestone estimates. Their product is 0.46, reduced slightly for leaderboard or label discontinuation. Meta’s download volume shows ecosystem strength, not near-frontier benchmark leadership. A single US or European near-frontier open-weight release causes a miss, so I am below the forecaster’s 0.50.

superforecaster-statistician · openai/gpt-5.6-sol

Base rate: 0.30 for a currently leading national bloc remaining first at all three annual snapshots of a fast-moving technology benchmark. I adjust upward because the supplied baseline shows a large 60–38 gap, several independent qualifying Chinese labs, and leadership since early 2025. I adjust downward for the strict three-leg conjunction, plausible near-frontier open-weight releases by non-Chinese labs, exact-date exposure, and automatic failure if the index or label disappears. The milestone probabilities multiply to 0.27 under independence; positive persistence across years raises the joint estimate, but not to 0.50. The key leaderboard indicators were unavailable, and no calibration history was supplied.