How Higgsfield Scales Generative Video with GMI Cloud

The Challenge

Powering Cinematic Video Generation at Scale

Higgsfield needed a flexible and powerful infrastructure partner to handle:

• High-throughput inference for real-time video generation and editing
  
• Rapid model iteration with cost-effective scaling
  
• Tailored GPU performance for visual fidelity and responsiveness

Before switching to GMI Cloud, Higgsfield encountered:

• Average model training time of 24 hours per run
  
• Inference latency of 800 ms under production load
  
• Compute costs growing 25% month over month on traditional cloud services
  

Generic cloud solutions fell short on cost, performance tuning, and support, especially for inference-heavy, media-centric workloads.

The Solution

GMI Cloud as a Necessary Infrastructure Partner

GMI Cloud delivered an infrastructure solution customized for the generative video stack:

• Access to the newest NVIDIA GPUs, enabling smooth rendering and scalable deployment
  
• Custom cluster and inference engine access, optimized for Higgsfield’s unique workload profile
  
• Right-sized resource planning to reduce idle spend and enable rapid scale-up
• Hands-on partnership, with GMI acting as an extension of Higgsfield’s technical team

Why the Partnership Worked for Generative Video

GMI Cloud delivered the performance and flexibility Higgsfield needed, while aligning infrastructure strategy with their long-term creative roadmap.

• Performance that matches creative vision: low latency, high output quality
  
• Agility to support rapid R&D: infrastructure that evolves with product and model iterations
  
• Aligned incentives: a partner invested in Higgsfield’s success, not just a vendor

Key metrics of improvement:

• 45% lower compute costs compared to prior providers
  
• 65% reduction in inference latency, enabling smoother real-time user experiences
  
• 200% increase in user throughput capacity, allowing Higgsfield to scale with demand

Comparison with Alternatives

Hyperscalers (AWS, Azure, GCP): High cost, rigid infrastructure, slow provisioning, generalized support‍

Other GPU providers: Lack of top-tier GPUs, inflexible contracts, limited customization‍

In-house infrastructure: High capital expenditure, operational complexity, slower time-to-market

Key Drivers Behind the Decision

• Immediate access to GMI Cloud’s infrastructure recognized as Reference Platform NVIDIA Cloud Partner
  
• Infrastructure tailored to real-time inference needs
  
• Transparent pricing aligned with startup growth
• Responsive team that adapts to product and engineering changes

Future Plans

Higgsfield is entering a major growth phase. As their user base expands and product features evolve, the need for scalable compute and holistic cloud solutions will only increase. From experimentation and model refinement to production-grade deployment and global delivery, Higgsfield sees GMI Cloud as a core part of their infrastructure roadmap.

The team expects to grow its reliance on GMI’s broader cloud capabilities, spanning orchestration, storage, and workload management, while continuing to scale inference workloads at the pace of user demand.

"We’re building the future of video creation, and GMI Cloud gives us the foundation to do it without compromise. As our infrastructure needs grow, we know they’ll grow with us."