https://peer.madiator.cloud/videos/watch/b3ce95d6-717d-4b4b-ad70-e7e998be23ea Learn how to set up Runpod Instant Clusters to work with a 1T parameter LLM. Runpod Instant Clusters provide distributed GPU computing across multiple Pods with high-speed networking infrastructure ranging from 100 Gbps to 3200 Gbps within a single data center. Each Pod receives a static IP assignment and automatic environment variable configuration including PRIMARY_ADDR, NODE_RANK, NUM_NODES, and WORLD_SIZE for seamless coordination between nodes. The system supports up to 8 network interfaces per Pod (eth1-eth8) for inter-node communication and integrates with distributed backends like NCCL and GLOO for efficient multi-GPU workloads. Technical implementation covers deployment patterns for PyTorch distributed training, Slurm job scheduling, and Axolotl fine-tuning workflows. The cluster architecture automatically designates a primary node and configures environment variables for multiprocessing libraries, enabling applications such as large language model training, federated learning systems, scientific simulations, and distributed data processing. Network interface management separates high-bandwidth inter-Pod communication from external traffic management, with NCCL_SOCKET_IFNAME utilizing all available interfaces by default for optimal bandwidth utilization across the cluster topology. Code blocks available to copy and paste from https://www.runpod.io/blog/how-to-run-moonshotais-kimi-k2-instruct-on-runpod-instant-cluster Want to start deploying your clusters on Runpod? Start today here. https://console.runpod.io/cluster Tue, 21 Jul 2026 20:33:00 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://peer.madiator.cloud https://peer.madiator.cloud/lazy-static/avatars/e2927aea-9e0a-454c-9327-68ec87b4da11.png https://peer.madiator.cloud/videos/watch/b3ce95d6-717d-4b4b-ad70-e7e998be23ea All rights reserved, unless otherwise specified in the terms specified at https://peer.madiator.cloud/about and potential licenses granted by each content's rightholder.