Conceptio › Archive › arXiv (All)
arXiv (All) open access

BitLLM: Efficient Low-Bit, Conversion-Hiding LLM Decoding on Mobile GPUs

Zheng, Hangyu et al.
arXiv (All) · Papers
Open Source ↗Direct PDF ↓
hardware-architecturemachine-learningoperating-systemsperformance
The rapid scaling of large language models (LLMs) has unlocked remarkable capabilities across various domains. However, deploying LLMs on mobile devices remains challenging because of their high computational and memory requirements. Low-bit quantization (e.g., 4-bit weights, 8-bit activations) can
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1536377
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive