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Posted: 2025-08-03 08:19:26 UTC
This article contains some claims that are falsified. While not everything in the article is false, please proceed with extreme caution and verify any critical information independently.
This article contains some claims that are falsified. While not everything in the article is false, please proceed with extreme caution and verify any critical information independently.
Status
Last Updated
2025-08-03 08:19:42 UTC
Verified By
Rollup News
Gradient.HQ's Parallax enables distributed LLM inference on heterogeneous hardware, integrating Macs and GPUs in a peer-to-peer network. It achieves faster speeds and lower latency compared to state-of-the-art systems, demonstrating efficient scalability and challenging the need for centralized data centers.
Distributed inference across heterogeneous hardware (Macs and GPUs)
Faster E2E speeds and lower latency compared to SOTA systems
Scalability demonstrated by matching 72B performance with 235B model
Peer-to-peer foundation for collective intelligence