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Open-source AI vs. closed-source AI may be the wrong debate.
Our latest research points to model ensembles outperforming individual frontier models.
@iamtrask explains why
Costs, stated plainly: the fusion runs $0.296/task (aug_2026_trio in the figure attached). GPT-5.6-sol solo scores 58.1% at $0.056/task.
Solo models remain the efficiency play. Fusions buy accuracy that no single model reaches at any price. That capability only exists as a fusion.
Costs, stated plainly: the fusion runs $0.296/task (aug_2026_trio in the figure attached). GPT-5.6-sol solo scores 58.1% at $0.056/task.
Solo models remain the efficiency play. Fusions buy accuracy that no single model reaches at any price. That capability only exists as a fusion.
The reason hasn't changed since DRACO. Different models make mistakes in anti-correlated ways. Where one slips, another catches it. The newest frontier models don't outrun the network. They join it and make it stronger.
Last week we told you we hadn't built fusions with the new models yet...
Well, we just did and it set a new SOTA on HealthBench. 🧵
https://t.co/RbM5EQRtds
Last month, fusions overtook every frontier model on the DRACO deep research benchmark. New frontier models have shipped since, so we re-ran it with the same last-gen fusions vs. GPT-5.6 and Opus 5. The lead still holds. And we haven't even built fusions with the new models yet… https://t.co/NOcF0SLqmT
Costs, stated plainly: the fusion runs $0.296/task (aug_2026_trio in the figure attached). GPT-5.6-sol solo scores 58.1% at $0.056/task.
Solo models remain the efficiency play. Fusions buy accuracy that no single model reaches at any price. That capability only exists as a fusion.