Q-Strata: Hierarchical Bit Allocation for Mixed-Precision Quantization of Mixture-of-Experts LLMs

arXiv:2608.30564 · cs.LG, cs.AI · Submitted 2026-08-31 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-08-31

Updated: 2026-08-31

Comments: EMNLP 2026 Long Paper - Main Conference

Code: https://github.com/snu-mllab/Q-Strata

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Calibration — 42× in this paper · explained in 9 episodes
• Quantization — 33× in this paper · explained in 15 episodes
• Perplexity — 23× in this paper · explained in 3 episodes
• Pruning — 13× in this paper · explained in 4 episodes
• Allocator — 9× in this paper · explained in 2 episodes
• Fine-Tuning — 8× in this paper · explained in 5 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Decode — 4× in this paper · explained in 2 episodes
• Mixture-of-Experts (MoE) — 3× in this paper · explained in 10 episodes
• Reconstruction Error — 3× in this paper · explained in 2 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Mixture-of-Experts (MoE) Models — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes

Sources

• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• WinoGrande: An Adversarial Winograd Schema Challenge at Scale
• Qwen3 Technical Report

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