Significant distributed AI benchmark achieved: 30.55 tokens/sec on GLM-5.2 (4-bit quantized) across six geographically distributed NVIDIA RTX 6000 Ada Generation GPUs connected via standard WAN infrastructure.
Key technical details (verified via leyten/shard GitHub repo):
- Implementation uses Python 3.10 with Redis for coordination
- Achieved without specialized networking hardware (InfiniBand/RDMA)
- Features custom quantization and load balancing
- Full code and methodology publicly available
Why this matters for decentralized AI:
- Demonstrates viable alternative to centralized GPU clusters
- Shows 4-bit quantization can maintain model quality at scale
- Provides blueprint for distributed inference using consumer hardware
Repository contains complete implementation details and benchmarks: https://github.com/leyten/shard