Beyond the spectacular figures which have focused attention, it is the evolution of Nvidia, from the GPU towards a systemic approach, which constitutes, in our eyes, the real subject of analysis.
Because Nvidia is no longer positioned just as a simple supplier of computing power. The group is now developing the complete architecture in which this power fits. Around the GPU, Nvidia has gradually built a complete environment with software libraries, orchestration tools, network interconnections, integrated systems delivered turnkey. This set now forms a coherent chain, optimized from end to end, which will be decisive in ensuring the future revenues of the company led by Jensen Huang.
For Amazon, Google and Microsoft, the choice is now the following: adopt a high-performance system, at the cost of increased dependence, or favor less efficient alternatives, at the risk of dropping out, while Nvidia captures a growing share of the value of computing.
This tension of course goes beyond just hyperscalers and permeates the entire ecosystem. Startups today build their products in environments largely structured by Nvidia standards. Historical competitors, such as Intel or AMD, no longer compete only on the performance of their chips, but on their ability to offer comparable systems.
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Announcements: product acceleration, an operational field that is opening up
Nvidia’s GTC 2026 will also have been an opportunity for Jensen Huang to clarify his product roadmap. The first sequence concerns the continuity of GPU architectures. After Blackwell, Nvidia is already preparing the next generation, Rubin, expected in the second half of 2026, then a subsequent architecture called Feynman. This cadence, now almost annual, encourages its customers to remain aligned with the developments of the platform.
The other structuring announcement relates to the integration of technologies from Groq. With LPUs, for Language Processing Units, Nvidia addresses inference, that is to say the model execution phase, more directly. Where GPUs dominate training, these new bricks aim for speed of response and efficiency in production.
At the same time, Nvidia is stepping up its offensive on general-purpose processors. The Vera CPU, presented as more versatile and less energy consuming, must play a key role in the orchestration of workloads.
These new products are accompanied by a strengthening of industrial partnerships, in particular with IBM and Adobe. The autonomous vehicle fleet project with Uber and Wayve by 2028 illustrates this gradual extension of uses, beyond just the data center.
Taken in isolation, these announcements are part of a classic product roadmap. Together, they reflect a formidable development strategy: Nvidia now covers all layers of computing, from hardware to final use. Beyond the spectacular income projections, it is this consistency which stands out as the main lesson of this 2026 edition.
