HIVE GPUs in Paraguay match H100 performance for 1.4B-parameter LLM training
HIVE•HIVE’s inaugural AI research project in Asunción optimized A40 GPUs to match H100 performance on 1.4B-parameter LLMs, achieving comparable throughput and latency for token-per-second benchmarks. Civil works on HIVE’s 100 MW Paraguay substation are complete, with commissioning set for summer 2026 and a Tier-III data center due H2 2027.
1. Inaugural AI GPU Performance Validation
HIVE collaborated with Columbia University researchers to run iterative training runs on A40 GPUs located in Asunción, Paraguay, demonstrating that optimized code produced throughput and latency metrics on 1.4 billion-parameter LLM pretraining equivalent to those on H100 GPUs after normalization. This proof of concept establishes a performance benchmark for intercontinental AI workloads across a 5,000-mile distance.
2. Paraguay Infrastructure Development
Civil works for HIVE’s 100 MW substation in Yguazú, Paraguay, are complete, with energization expected in September 2026. Construction of a new Tier-III data center will begin in Fall 2026, targeting a ready-for-service date in the second half of 2027, laying the groundwork for the company’s HPC/AI Gigafactory.
3. Commercial Implications for HIVE’s AI Platform
By validating A40 performance parity with H100 chips through advanced code optimizations, HIVE bolsters the commercial potential of its GPU-accelerated AI infrastructure, positioning Paraguay as a competitive node in global AI computing. This milestone may drive customer interest in geographically distributed compute solutions and support future revenue growth from AI services.
4. Leadership Vision and Future Plans
HIVE’s executive team highlights the significance of distributed AI infrastructure, emphasizing the company’s strategy to integrate power, data center design, and software stacks. The successful trial underpins plans to expand GPU-accelerated operations while leveraging Paraguay’s strategic location and green energy resources to participate directly in the global AI economy.
