
Tech • AI • Robotics • Game
Vinted says its roughly €10 billion in annual sales is still small against the €450 billion spent on new clothing in Europe each year. Chief executive Thomas Plantenga argues that gap shows second-hand remains far from the default consumer behavior. By some measures, Vinted has become the biggest online clothing seller in France, yet management still frames the company as early in its market penetration. The pitch is less victory lap than scale argument: resale is growing, but the core apparel market remains overwhelmingly primary retail.
Thomas Plantenga, a Dutch executive, originally arrived in Vilnius for a five-week consulting assignment linked to Insight Ventures and stayed to run the company. He found a technically strong founding team but a business in acute distress, then put forward a restructuring plan centered on survival. That plan became the basis for a long-term leadership role rather than a temporary advisory stint. The episode is now presented as a case study in how investor intervention, operational discipline and founder alignment can reset a startup’s trajectory.
The turnaround at Vinted was described as severe and immediate: offices outside Lithuania, including in the United States and Paris, were closed and activity was centralized in Vilnius. The company also made deep cost cuts to preserve cash and simplify execution. Management’s conclusion is that concentration, rather than dispersed expansion, gave the business a viable operating base. That retrenchment helped turn a near-crisis into a platform for cross-border European growth.
For Vinted, cross-border scale in Europe remains constrained by fragmented national regulation despite the promise of a single market. Plantenga argues that differing rules raise operating complexity and slow execution for consumer internet companies trying to expand across borders. The critique is notable because Vinted is often cited as a rare European marketplace success story. Its message is that even winners still pay a material penalty for regulatory inconsistency across the continent.
Nvidia is depicted as operating at extraordinary scale, with claims of around $1 billion in daily revenue and roughly 75% gross margin. Forecasts cited for 2028 put revenue near $627 billion, underlining why competitors and customers want alternatives. Such economics make Nvidia both a supplier and a strategic dependency for the AI sector. The richer the company becomes, the stronger the incentive for rivals to attack its position on price, supply and leverage.
Competitive pressure is broadening beyond classic chipmakers, with Google expanding TPU deployments and seeking external demand. Reports that Anthropic could buy billions of dollars of TPU hardware suggest hyperscaler silicon is becoming commercially credible outside captive use. That matters because it would turn internal infrastructure programs into direct competitive products. For Nvidia, the threat is not only silicon performance but the emergence of alternative ecosystems backed by cloud distribution.
The field of challengers now includes OpenAI, which is portrayed as developing its own processor, and Chinese groups such as DeepSeek, which are shifting toward domestic chips. The strategic logic is similar across markets: reduce dependence on Nvidia GPUs, secure supply and tailor hardware to model workloads. In China, geopolitics adds urgency to the localization push. In the United States, frontier labs increasingly see chip design as part of long-term bargaining power.
Despite the attacks on its dominance, Nvidia still benefits from the depth of its software stack and the switching costs built over more than a decade. AI labs have optimized tools, workflows and engineering teams around Nvidia platforms, making migration expensive and risky. Earlier alternatives, including Amazon Trainium, were often seen as less capable in their first iterations, reinforcing incumbency. Nvidia is also using acquisitions, open-source software, financing structures and customer pressure to keep that moat intact.