DyMoE: Dynamic Expert Orchestration with Mixed-Precision Quantization for Efficient MoE Inference on Edge | ScienceToStartup | ScienceToStartup

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References (27)

[1]

SparseServe: Unlocking Parallelism for Dynamic Sparse Attention in Long-Context LLM Serving

2025Qihui Zhou, Peiqi Yin et al.

[2]

Qwen3 Technical Report

2025An Yang, Anfeng Li et al.

[3]

FloE: On-the-Fly MoE Inference on Memory-constrained GPU

Founder's Pitch

"A dynamic mixed-precision quantization framework for efficient Mixture-of-Experts inference on edge devices."

Efficient MoE Inference•Score: 5•View PDF ↗

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DyMoE: Dynamic Expert Orchestration with Mixed-Precision Quantization for Efficient MoE Inference on Edge

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References (27)

Founder's Pitch

"A dynamic mixed-precision quantization framework for efficient Mixture-of-Experts inference on edge devices."

Commercial Viability Breakdown

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DyMoE: Dynamic Expert Orchestration with Mixed-Precision Quantization for Efficient MoE Inference on Edge

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References (27)

Founder's Pitch

"A dynamic mixed-precision quantization framework for efficient Mixture-of-Experts inference on edge devices."

Commercial Viability Breakdown

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