From Compute Accumulation to Compute Orchestration: How Phancy Is Redefining China's AI Infrastructure

The Inflection Point Nobody Saw Coming

For years, the race in AI infrastructure was simple: whoever had the most chips won. More GPUs meant more power, more training capacity, and ultimately, more competitive advantage. But that era is over — and a new one has quietly begun.

On June 15, 2026, global growth consulting giant Frost & Sullivan released its "2026 AI Infrastructure Orchestration Platform White Paper", and its findings sent a clear signal to the industry: the future of AI infrastructure is no longer about raw compute — it's about how intelligently you orchestrate it.

The Dirty Secret of China's AI Boom

Beneath the surface of China's explosive AI growth lies a structural crisis. As large model applications scale rapidly across enterprises, a "multi-chip coexistence" problem has emerged. Companies are running hardware from NVIDIA, Ascend, Cambricon, Hygon, and a growing list of domestic chip vendors — all under one roof, all with incompatible software stacks.

The result? GPU utilization rates persistently below 30%. That means more than 70% of expensive compute hardware sits idle or underused at any given time. Add fragmented software stacks, rising model adaptation complexity, and hardware heterogeneity, and you have a recipe for massive inefficiency — a bottleneck that threatens to slow China's AI ambitions just as they are hitting their stride.

Enter Phancy: The Orchestration Pioneer

Against this backdrop, Phancy Group (6682.HK) has emerged as the standout solution. The Frost & Sullivan white paper assessed mainstream AI infrastructure platforms across three core dimensions: heterogeneous support, fine-grained control, and production-grade execution — and awarded Phancy's Rise vGPU the coveted Tier 1 Leading Platform designation, the highest maturity tier in the entire evaluation.

This is not a minor accolade. Tier 1 status means Rise vGPU simultaneously meets all three criteria — something few platforms in the market can claim.

What Makes Rise vGPU Different?

Rise vGPU fundamentally transforms AI infrastructure from fragmented, low-efficiency device-level management into a unified software-defined control plane. Here's what that means in practice:

• Comprehensive Heterogeneous Management — Unified onboarding across 10+ mainstream GPU/NPU vendors including NVIDIA, Ascend, Cambricon, and Hygon
• Ultra-Fine Resource Partitioning — Sub-GPU level compute and MB-level memory granularity slicing
• Dramatic Utilization Improvement — GPU utilization jumps from the industry average of below 30% to 70%–90% through safe oversubscription and time/space multiplexing
• Intelligent Precision Scheduling — Multi-dimensional algorithms based on priority, topology, load, and resource awareness
• Production-Grade SLA Assurance — A Deterministic Execution Layer that delivers committed, auditable SLA guarantees for critical inference workloads
• Full Lifecycle Operability — Comprehensive monitoring, metering, and cost allocation that turns GPU resources into truly operable digital assets

ModelHub: The Missing Piece of the Puzzle

Rise vGPU handles the compute layer — but what about the model layer? That's where Phancy ModelHub comes in. In the white paper's enterprise-grade model management platform evaluation, ModelHub achieved the highest Overall Score across all assessed platforms.

ModelHub excels in three key areas:

• Model & Chip Compatibility
• Execution Stability & Performance
• Model-GPU Coordination & Scheduling

Together, Rise vGPU and ModelHub form a complete full-stack AI infrastructure — from compute resource scheduling all the way to business delivery. The combination creates a seamless closed-loop process covering model onboarding, deployment optimization, inference services, and version governance, dramatically lowering the barrier to enterprise AI deployment.

A CEO's Vision

Dr. Dai Wenyuan, Founder & CEO of Phancy, put it plainly:

"The Frost & Sullivan white paper accurately captures the inflection point in AI infrastructure development. We believe the next wave of competitiveness in the AI industry will come from systematic improvements in compute orchestration efficiency. We will continue to focus on heterogeneous compute unified scheduling and model ecosystem operations, working closely with customers and industry partners to advance China's AI industry from 'compute accumulation' to a true 'compute orchestration' era."

This isn't just corporate speak. Phancy's track record backs it up — the company has been ranked #1 in China's Machine Learning Platform Market for 8 consecutive years, and in early 2026, reported revenues exceeding RMB 7 billion while turning profitable.

Why This Matters Beyond China

The heterogeneous AI infrastructure challenge is not unique to China. As the global AI industry accelerates, every major enterprise faces the same dilemma: a growing zoo of AI chips, each with its own ecosystem, each demanding its own software stack. The ability to orchestrate across all of them — efficiently, reliably, and at scale — is fast becoming the defining competitive advantage in enterprise AI.

Phancy's recognition by Frost & Sullivan is a signal that the "compute orchestration" paradigm is not a future trend — it is happening now, and China is leading the way.

The Bottom Line

The age of simply throwing more GPUs at AI problems is over. The winners of the next AI era will be those who can do more with what they have — orchestrating heterogeneous compute resources with precision, intelligence, and efficiency. Phancy's Rise vGPU and ModelHub represent exactly that capability, and their Tier 1 recognition from Frost & Sullivan is a landmark moment for China's AI infrastructure industry.

From compute accumulation to compute orchestration — the revolution is already here.