Why NVIDIA dominates despite low developer program scores

In the competitive landscape of technology vendors, developer programs are often seen as essential for building robust ecosystems. Our Developer Program Benchmarking research consistently reveals a puzzling phenomenon: NVIDIA. Its developer program scores lower than average across all vendors we benchmark in terms of engagement and satisfaction for two consecutive years. Yet, the company maintains strong leadership in market capitalisation, having recently hit a record high in shares. 

This paradox highlights a broader industry insight; dominance doesn't always stem from developer program polish. Instead, it can come from holistic ecosystem strategy. In this blog, we explore what has worked for NVIDIA and what other vendors, particularly silicon-focused players such as AMD, Intel, and Qualcomm, can learn from their model.

The CUDA ecosystem

NVIDIA’s most significant developer engagement lever is not its formal program, but the CUDA (Compute Unified Device Architecture) ecosystem. Launched in 2006, CUDA has become the gold standard for GPU programming in AI, HPC, and scientific computing. It’s a comprehensive ecosystem of libraries, including cuDNN for deep learning and cuBLAS for linear algebra, along with deep integrations with frameworks such as PyTorch and TensorFlow. This makes CUDA not only powerful but also incredibly sticky. Developers and researchers who build with it rarely look elsewhere, because switching means losing access to the world’s most mature and optimised GPU platform.

What really sets CUDA apart is its network effect. It’s taught in universities, required in job postings, and baked into the workflows of thousands of startups and research labs. According to NVIDIA, over 4.5 million developers now use CUDA, up from 1.8 million in 2020. That’s a 150% increase in just a few years. That growth is self-reinforcing: more users mean better community support, more shared code, and more third-party tools, an ecosystem momentum few competitors have matched.

However, this community-driven approach can also present strategic vulnerabilities. NVIDIA has limited control over the developer experience, support quality, or messaging within this ecosystem. Much of this knowledge transfer is happening through informal channels or community groups, rather than optimised pathways. Silicon vendors like AMD and Intel, by comparison, have struggled to build similarly mature software ecosystems around their hardware offerings.

University partnerships and training

NVIDIA has strategically invested in academic partnerships that create a continuous pipeline of developers already familiar with their technology. Its partnership with the University of Florida is a prime example: a $70 million initiative that resulted in the HiPerGator 3 supercomputer, powered by NVIDIA DGX SuperPOD systems. Beyond infrastructure, this collaboration includes curriculum development and access to the latest GPU tools, embedding NVIDIA’s technology directly into teaching and research pipelines.

This effort is mirrored in the NVIDIA Deep Learning Institute (DLI) University Ambassador Program. The program equips faculty with cloud-based GPU labs and ready-made teaching kits to deliver hands-on training in CUDA and AI. Rather than relying on documentation or forums, NVIDIA meets students where they are, inside classrooms, with real tools and real use cases. 

This early career intervention is one of NVIDIA’s most successful developer strategies, and one that bypasses traditional program metrics entirely. For other vendors, especially those with strong hardware portfolios but weaker developer engagement, replicating this academic integration could yield significant returns in loyalty and talent development. A key advantage for other vendors is the ability to combine this intervention strategy with a superior formal developer program which accelerates developers' success and advocacy once they enter the workforce.

NVIDIA’s full-stack integration strategy

Beyond chips and training, NVIDIA’s edge lies in owning the full AI stack, from hardware to software to networking. Unlike competitors who sell only silicon, NVIDIA delivers integrated systems, such as the DGX SuperPOD and AI Factory reference architectures, which combine GPUs, NVLink switches, SDKs like TensorRT, and orchestration tools like NVIDIA Run:AI. These aren’t just hardware bundles; they’re turnkey solutions that enterprises can drop into production environments with minimal configuration. This vertical integration creates seamless workflows and performance optimisations that generic silicon providers can’t easily match.

Competitors like AMD and Intel largely remain focused on component-level sales, often relying on third-party or open-source tooling to complete the developer stack. The result is a fragmented experience that can frustrate developers and delay deployments. NVIDIA’s approach, by contrast, offers plug-and-play performance for production AI environments, which shortens time-to-value and raises switching costs.

While the technology integration is seamless, the developer experience of learning, troubleshooting, and optimising can heavily rely on informal, community support if they are not actively involved in a partner university program. Competitors exploring full-stack integrations can consider leveraging their more comprehensive developer program to support effective documentation, responsive support networks, and clear migration guides.

Strategic implications for technology vendors

NVIDIA’s success despite low developer program satisfaction scores highlights a fundamental industry lesson: true developer loyalty stems not from polished portals or responsive forums, but from building a cohesive and indispensable ecosystem. This includes proprietary SDKs, full-stack integration, academic partnerships, and hands-on training, all of which create long-term reliance and lower the barrier to entry for developers. Developer programs support developers and encourage long-term engagement, but ecosystems draw people in.

For silicon vendors and technology leaders seeking to expand their developer base, this means rethinking developer engagement as a long-term ecosystem investment rather than a series of touchpoints. A well-supported, fully integrated platform, even if it's not the most performant, can win developer mindshare by helping teams ship faster and with more confidence. For shareholders, the implication is clear: ecosystem depth is not just a differentiator, but a strategic advantage. Those who build ecosystems, not just programs, will define the next era of technological leadership.

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About the author

Bleona Bicaj, Senior Market Research Analyst

Bleona Bicaj is a behavioural specialist, enthusiastic about data and behavioural science. She holds a Master's degree from Leiden University in Economic and Consumer Psychology. She has more than 7 years of professional experience as an analyst in the data analysis and market research industry.