Twitter co-founder Jack Dorsey publicly backed venture capitalist Chamath Palihapitiya’s call to fully embrace open source artificial intelligence (AI).
Dorsey replied “yes” to Palihapitiya’s post warning that US restrictions on open models would be economically ruinous.
Palihapitiya argued that closing off open source AI would force American firms to pay $26 to $56 per million tokens for intelligence that rivals abroad can buy for $0.50 to $1. He called that gap unsustainable.
The AI Pricing Gap Behind the Debate
Palihapitiya’s argument rests on a widening split between cost and capability. Open weight models have closed much of the performance gap with proprietary systems, yet the price difference remains enormous.
Chinese labs have driven that shift. Beijing-based Moonshot AI’s new model Kimi K3 topped coding benchmarks this month, rattling US chip stocks.
Other releases point to a broader narrowing capability gap between Chinese and American systems.
Palihapitiya frames this as untenable if AI truly underpins future economic activity, since American businesses would face a structural cost disadvantage against global competitors.
He posed the dilemma bluntly, saying intelligence cannot be the engine of the economy and a premium import at the same time.
A Military Argument, Not Just an Economic One
Palihapitiya extended his case to national defense. Paying dozens of dollars per million tokens to defend US systems, while adversaries attack for far less, carries the same imbalance, he said.
David Sacks echoed that view. He agreed with researcher Sebastian Mallaby that dangerous capability will soon spread freely regardless of policy.
Mallaby pointed to the same Mythos-level cyber capability concerns already flagged around Anthropic’s Claude Mythos model, arguing the world moves quickly from almost nobody holding that power to nearly everyone holding it.
Sacks had predicted Chinese models would reach advanced cyber capability within months. He noted that Washington itself staggered its GPT-5.6 release over similar security worries, yet gatekeeping still failed to slow foreign progress. His answer is AI-powered cyberdefense rather than restriction.
Washington’s AI Gatekeeping Dilemma
The exchange lands as US policymakers debate how tightly to control advanced models. Officials have floated plans to vet AI models before release, hoping to manage security risk without ceding ground to China.
Sacks argues that approach cannot work once comparable capability is downloadable worldwide.
Palihapitiya’s framing pushes the same conclusion from an economic angle. Both men land on restriction, not openness, as the greater risk to US competitiveness.
Dorsey’s one-word endorsement carries weight given Block’s own open source AI agent, Goose, which he has championed publicly for years.
Whether Washington heeds the warning, or keeps restricting access, will shape how American firms compete on cost this year.
Palihapitiya’s post had drawn hundreds of thousands of views within hours, a sign the debate resonates well beyond Silicon Valley.
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