How ProSieben scaled Germany’s Next Top Model TOPSHOT for real-time AI portraits with Gcore
- October 1, 2025
- 2 min read
To celebrate the 20th season of Germany’s Next Top Model (GNTM), ProSieben’s marketing team launched GNTM TOPSHOT, an AI-powered feature in the Joyn app that instantly transforms user photos into studio-grade, show-inspired portraits.
At broadcast scale, the challenge was steep: handle massive primetime spikes, deliver results instantly, and guarantee strict EU privacy compliance. To make it possible, ProSieben turned to Gcore Everywhere AI.
“We needed something that could scale on demand, deliver in seconds, and keep data local. Gcore’s infrastructure let us bring a creative idea to life - without breaking the user experience.”
- Simon Hawe, Technical Lead, Joyn
The challenge: broadcast-scale creativity in real time
TOPSHOT had to satisfy five tough, non-negotiable requirements:
- Primetime surges. Usage surged before, during, and after live broadcasts across Germany, Austria, and Switzerland.
- Ultra-low latency. Fans expected results within 5 - 10 seconds per portrait, end-to-end.
- Privacy by design. Joyn deletes all photos immediately to keep user data truly private - no caching, no storage. Caching wasn’t an option; every request had to be generated fresh.
- High fidelity. Each portrait required a ~100-stage pipeline for segmentation, relighting, skin/pose preservation, and compositing, to match GNTM’s signature aesthetic.
- Frictionless UX. No login required. The feature had to “just work,” even on mobile connections.
Turning fans into models in real time
ProSieben needed an inference platform that was scalable, privacy-compliant, and easy to integrate. Gcore Everywhere AI delivered:
- One endpoint, nearest node. Smart Routing automatically sent each request to the closest GPU endpoint, minimizing jitter and wait times.
- Autoscaling GPUs. Serverless orchestration spun GPU capacity up or down in real time, handling unpredictable primetime peaks.
- EU-ready deployments. Hybrid support (on-prem, Gcore Cloud, public cloud) gave ProSieben full flexibility on data residency.
- Optimized for image workloads. Everywhere AI ran TOPSHOT’s complex pipelines on NVIDIA H100, A100, and L40S GPUs - excellent for generative image models.
“Our biggest challenge was combining visual fidelity with real-time response. Gcore’s Smart Routing and auto-scaling made that possible at primetime scale.”
- Benjamin Risom, Chief Product Officer, Joyn
The architecture allowed ProSieben to:
- Route all traffic through a single inference endpoint, fronted by their own load balancer
- Keep portrait generation under 10 seconds - even during broadcast surges
- Meet strict privacy guarantees: no logins, no storage of inputs or outputs
- Deliver a seamless experience inside the Joyn app
TOPSHOT went live with five portrait scenes in April 2025, with three more added weeks later.
“We could focus on the creative, knowing the infrastructure would scale with us. That made it possible to deliver something really special for our viewers.”
— Sebastian v. Wyschetzki, Creative Lead, Seven.One Entertainment Group
Real-time engagement, broadcast scale
TOPSHOT launched into a season already driving cultural buzz.
- The GNTM Season 20 finale (June 19, 2025) drew 3.87M viewers with a 22.4% share in the 14 - 49 demo.
- Joyn saw 10M viewers in April 2025 (+80% YoY) and a 40% increase in watch time in Q1 2025 YoY.
- TV Total host Sebastian Pufpaff demoed TOPSHOT live on air, praising the visuals and sparking organic uptake.
- Trade press highlighted the “scalable Gcore infrastructure” behind the feature.
“Gcore’s platform gave us regional performance, privacy control, and GPU scaling without the heavy lifting of building and managing infrastructure ourselves.”
— Paolo Garri, Infrastructure Architect, Joyn
What’s next?
Building on TOPSHOT’s success, ProSieben is playing with new potential fan-facing AI experiences: video portraits, real-time filters, or stylized animations. With Gcore’s flexible infrastructure, the team is free to keep experimenting without re-architecting.
“The success of TOPSHOT showed us what’s possible. Now we’re asking: how far can we take this?”
— Jutta Meyer, Executive VP Marketing & Creation, Seven.One Entertainment Group
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Leonardo AI delivers high-speed, global content creation with Gcore AI services
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What really sets Gcore apart though, is the hands-on, personalized support. Their team really understands our setup and helps us to optimize it to our specific needs.James Stewart, DevOps Engineering Manager, Leonardo.AiDelivering real-time creation with top-tier AI infrastructurePartnering with Gcore helps Leonardo to maintain its famously rapid pace of development and consistently deliver innovative new features to Leonardo.Ai users.With Gcore, we can spin up GPU nodes instantly and trust that they’ll work reliably and consistently. Knowing that Gcore has the capacity that we need, when we need it, allows us to quickly and confidently develop new, cutting-edge features for Leonardo customers without worrying whether or not we’ll have the GPUs available to power them.James Stewart, DevOps Engineering Manager, Leonardo.AiThe team now uses Terraform to provision GPUs on demand, and containerised workflows to “go fast” when deploying the suite of Gcore AI services powering Leonardo.Ai.Powering global AI creativityGcore GPU Cloud has become part of the backbone of Leonardo AI’s infrastructure. By offloading infrastructure complexity to Gcore, the Leonardo AI team can stay focused on their customers and innovation.Our partnership with Gcore gives us the flexibility and performance to innovate without limits. We can scale our AI workloads globally and keep our customers creating.James Stewart, DevOps Engineering Manager, Leonardo.AiReady to scale your AI workloads globally? 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Riga Technical University accelerates genomic research with Gcore GPU Cloud
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By leveraging Cloud GPUs, they identified optimal setups for accelerating genomic workflows.Comparison of CPU vs. GPU: Genome sequencing that previously took over 650 minutes on CPUs was reduced to under 30 minutes with GPU-powered processing.Testing NVIDIA GPUs: Experiments with GPU configurations provided insights into computational efficiency, with findings indicating that scaling up GPUs did not always equate to faster processing.Future discussions with NVIDIA: Gcore’s collaboration enabled further optimizations in GPU usage for genomic analysis.A comparison of CPU and GPU computing times: while CPU processing time exceeded 650 minutes, it could be significantly reduced to under 30 minutes for all tested configurations when using fq2bam H100Faster, scalable, and cost-effective genomic researchNVIDIA H100 GPUs, provided as-a-service by Gcore, delivered graphics processing units with a compute performance that is revolutionizing cloud infrastructure. They are also specifically designed with the power required for high-performance computing tasks such as computational genomics. “It was important for us to see how fast inference runs on the H100,” says Edgars Liepa, “We didn’t customize the model but instead used one developed by NVIDIA, which was already well suited for our task.”The collaboration between RTU HPC, BMC, and Gcore delivered significant benefits to the research program, including:Significant reduction in processing time: Variant calling tasks were completed up to 50x faster.Cost savings with on-demand GPUs: Eliminating upfront hardware investments while optimizing computing costs.Scalable infrastructure: The ability to dynamically allocate resources based on real-time needs.Data sovereignty and security: Genomic data was processed within a compliant, secure cloud environment.The measured processing times of the tested H100 GPUs in detail: the processing time ranged from 13 minutes for haplotypecaller H100 with 2 GPUs used to just under 90 minutes for Deepvariant H100 with 8 GPUs used, indicating that GPU overhead can slow down the processing time when the effective memory limit is reached“It’s not just about going faster,” Liepa adds. “It’s about enabling analysis at a national scale. The AI models are there—but without the right compute power, they’re just theory.”Advancing high-performance genomics in the Baltics and beyondBy leveraging Gcore’s Cloud GPUs, RTU HPC has established a model for scalable, cost-effective genomic research, and this is only the beginning. Now that the speed and flexibility has been proven on genomics processing, RTU HPC plan to broaden AI applications even further.Wider adoption of Cloud GPUs in genomics: RTU HPC is considering Cloud GPUs expansion for broader research applications.Future collaboration with Gcore: Optimization of GPU configurations will continue, and RTU HPC plans to explore AI Inference opportunities with Gcore Everywhere Inference for genomic workloads.Global implications: BMC’s work with the 1+ Million Genomes Project, an EU-wide initiative to make genomic information more accessible for diagnosis and treatment, contributes to international research efforts.The benchmark test results for H100 GPUs using 2, 4, or 8 GPUs: fq2bam and haplotypecaller achieved the shortest processing times on average and comparatively consistent results across 2, 4, and 8 GPUsPioneering AI-powered genomics with sovereign cloud infrastructure“This is the future of AI in healthcare: fast, flexible, sovereign,” says Liepa. “Gcore gave us the infrastructure to make it real—not just for today, but for what comes next.”As AI continues to transform life sciences, the ability to combine cutting-edge GPU performance, regional data compliance, and on-demand scalability is emerging as the key to competitive advantage—not just for companies, but for countries.“We’re proud to support Latvia’s vision for AI-powered genomics,” says Vsevolod Vayner, Product Director of Edge & AI Cloud at Gcore. “This project is a blueprint for how nations can lead in biotech innovation without giving up digital sovereignty.”Find out more about how Gcore Cloud GPUs can enhance your high-performance computing projects.Try Gcore Cloud GPUs
LetzAI rapidly scales AI-powered image generation for global users
Everywhere Inference reduces the latency of our output and enhances the performance of AI-enabled apps, allowing us to optimize our workflows for more accurate, real-time results.Misch Strotz, CEO and co-founder, LetzAIA futuristic tram journey, blending reality and imagination, created with LetzAI. Destination: To the MoonLaunched as a skunkworks project from within Neon Internet, LetzAI is quickly becoming a go-to platform for high-quality AI-generated images. With a mission to democratize and personalize AI-powered image generation, it has emerged as one of the most popular and high-quality options on the market. To support its rapid growth and scale seamlessly, LetzAI partnered with Gcore for advanced AI and cloud infrastructure.Global GPU shortages threaten to derail a new AI image generation ideaIn 2023, Neon Internet CEO and co-founder Misch Strotz was struck by a clever idea: give Luxembourg residents the power to easily generate local images using AI. Within a month, Luxembourg-focused LetzAI V1 went live.Encouraged by strong local demand, Strotz and his team began working on a global version of the platform. The vision? An opt-in AI platform empowering brands, creators, artists, and individuals to unlock endless creative possibilities by adding their own images, art styles, and products. “Other AI platforms scrape the internet, incorporating people and their content without permission. We wanted to put the choice and power in each person’s hands,” Strotz explains.Before long, the team began working on V2. In addition to generating higher quality and more personalized AI-generated images, V2 would drive consistency across objects, characters, and styles. After uploading their own photos and creating their own models, users can blend them with other models created by the community to create an endless number of unique images.However, LetzAI faced a significant hurdle in training and launching V2—a global GPU shortage. With limited resources to train its models, LetzAI needed a reliable partner to help evolve its AI-driven platform and keep it operating smoothly.Finding a trusted, Europe-based AI partnerIn the search for a fitting partner, Strotz spoke to major vendors including hyperscalers and various Europe-based providers. Meeting Gcore’s product leadership team made the decision clear. “It was amazing to meet executives who were so knowledgeable about technology and took us seriously,” recalls Strotz.Gcore’s approach to data security and sovereignty further solidified the decision. “We needed a trusted partner who shared our commitment to European data protection principles, which we incorporated into the development of our platform” he continues.Maximizing AI efficiency by training on local GPUsLetzAI opted for Gcore’s state-of-the-art NVIDIA H100 GPUs in Luxembourg. “This was the perfect option, allowing us to keep our model training and development local. With Gcore, we can rent GPUs rather than entire servers, making it a far more cost-effective solution by avoiding unnecessary costs like excess storage and idle server capacity,” Strotz explains. This approach provided flexibility, efficiency, and high performance, tailored specifically for AI workloads.LetzAI was able to adapt its app to run in containers, configure model training tasks to run on GPU Cloud, and use Everywhere Inference for image generation and upscaling. “Everywhere Inference reduces the latency of our output and enhances the performance of AI-enabled apps, allowing us to optimize our workflows for more accurate, real-time results,” Strotz says.In just two months, LetzAI V2 launched to serve users around the world. And Strotz and team were already developing its successor.Empowering creativity with scalable, high-performance AI infrastructureWith Gcore’s continued support, LetzAI quickly deployed V3. “The Gcore team was incredibly responsive to our needs, guiding us to the best solution for our evolving requirements. This has given us a powerful and efficient infrastructure that can flex according to demand,” says Strotz.Running V3 on Gcore means LetzAI users experience fast, reliable performance. Artists, individuals, and brands are already putting V3 to use in interesting ways. For example, in response to what LetzAI calls its ‘AI Challenges’, a Luxembourg restaurant chain prompted residents to create thousands of images using its model of a pizza.In another example, LetzAI teamed with digital agency LOOP to dress PUMA’s virtual influencer and avatar, Laila, in a Moroccan soccer jersey. According to Strotz, “PUMA had struggled to make clothing look realistic on Laila. When they saw our images, they said the result was 1,000 times better than anything they had tried.”That wasn’t the only brand intrigued by V3’s possibilities. After LetzAI posted V3-generated images of models wearing Sloggi underwear, Sloggi’s creative agency STAN Studios asked LetzAI to generate more images for market testing.Always looking for new ways to support creators, LetzAI also launched its Image Upscaler feature, which enhances images and doubles their resolution. “Our creators can now resolve common AI image issues around quality and resolution. Everywhere Inference is pivotal in delivering the power and speed needed for these dynamic image enhancements,” notes Strotz.Platform evolution and AI innovation without limitsAs its models exceed user expectations worldwide, LetzAI can rely on Gcore to handle a high volume of requests. Confident about generating a limitless number of high-quality images on the fly, LetzAI can continue to scale rapidly to become a sustainable, innovation-driven business.“As we further evolve—such as by adding video features to our platform—our partnership with Gcore will be central to LetzAI’s continued success,” Strotz concludes.
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