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If you're building multi-agent systems, you've probably already noticed how fast orchestration overhead compounds. KV cache grows, inference concurrency spikes, and suddenly GPU memory and bandwidth become a problem.

Why does that happen? Running planner, retrieval, memory, and reasoning agents in parallel puts real pressure on infrastructure. This is where multi-agent orchestration becomes a serious compute workload. One slowdown in throughput and the entire pipeline slows down.

The NVIDIA H200 Tensor Core GPU was built for workloads like this. 141GB HBM3e VRAM and massive memory bandwidth, designed for long-context, memory-intensive AI systems operating at scale.

The best part? H200 GPUs are available on demand at $2.16/hr on Ocean Network: https://dashboard.oncompute.ai/


https://x.com/oceanprotocol/status/2056752487806439457?s=46&t=sfyIS0XeZHZd-w68hBLkvw
Ocean Network - Decentralized P2P Compute Network Run pay-per-use compute jobs on Ocean Network with competitive GPU pricing, editor native workflows, escrow-protected payments, and local outputs.
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