Revolutionizing LLM Inference: RTX 5070 Ti Ray Tracing Cores Achieve 218x Speedup
infrastructure#gpu📝 Blog|Analyzed: Apr 9, 2026 16:34•
Published: Apr 9, 2026 15:01
•1 min read
•r/LocalLLaMAAnalysis
This brilliant hack demonstrates an incredible leap forward in consumer hardware optimization for Large Language Models (LLM). By cleverly utilizing idle ray tracing cores to handle Mixture-of-Experts routing, the developer has drastically reduced VRAM usage and latency while maintaining stellar accuracy. It is a fantastic testament to the AI community's ingenuity in squeezing every ounce of performance out of accessible consumer GPUs.
Key Takeaways
- •Achieved a staggering 218x faster routing and 731x less VRAM usage during LLM inference on a consumer RTX 5070 Ti.
- •Discovered that MoE experts actually specialize by syntactic type rather than specific topics like science or history.
- •The entire hardware-accelerated routing process runs efficiently with only a minimal +1.5% perplexity hit and 95.9% accuracy.
Reference / Citation
View Original"Takes the routing decision in MoE models (which experts process which tokens)... Uses the GPU's dedicated ray tracing hardware to find the right experts... O(log N) instead of O(N) — hardware-accelerated"
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