PDF Viewer

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $9K - $13K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (25)

[1]
Edge Deployment of Small Language Models, a comprehensive comparison of CPU, GPU and NPU backends
2025Pablo Prieto, Pablo Abad
[2]
Production-Grade Local LLM Inference on Apple Silicon: A Comparative Study of MLX, MLC-LLM, Ollama, llama.cpp, and PyTorch MPS
2025Varun Rajesh, Om Jodhpurkar et al.
[3]
MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe
2025Tianyu Yu, Zefan Wang et al.
[4]
GTA: Grouped-head latenT Attention
2025Luoyang Sun, Jiwen Jiang et al.
[5]
PLM: Efficient Peripheral Language Models Hardware-Co-Designed for Ubiquitous Computing
2025Cheng Deng, Luoyang Sun et al.
[6]
Densing law of LLMs
2024Chaojun Xiao, Jie Cai et al.
[7]
A Review on Edge Large Language Models: Design, Execution, and Applications
2024Yue Zheng, Yuhao Chen et al.
[8]
The Llama 3 Herd of Models
2024Abhimanyu Dubey, Abhinav Jauhri et al.
[9]
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
2024Zhihong Shao, Damai Dai et al.
[10]
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
2024Zechun Liu, Changsheng Zhao et al.
[11]
TinyLlama: An Open-Source Small Language Model
2024Peiyuan Zhang, Guangtao Zeng et al.
[12]
LLM in a flash: Efficient Large Language Model Inference with Limited Memory
2023Keivan Alizadeh-Vahid, Iman Mirzadeh et al.
[13]
Llama 2: Open Foundation and Fine-Tuned Chat Models
2023Hugo Touvron, Louis Martin et al.
[14]
AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration
2023Ji Lin, Jiaming Tang et al.
[15]
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day
2023Chunyuan Li, Cliff Wong et al.
[16]
Holistic Evaluation of Language Models
2023Percy Liang, Rishi Bommasani et al.
[17]
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
2023Lingjiao Chen, M. Zaharia et al.
[18]
Efficiently Scaling Transformer Inference
2022Reiner Pope, Sholto Douglas et al.
[19]
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
2022Elias Frantar, Saleh Ashkboos et al.
[20]
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
2022Tri Dao, Daniel Y. Fu et al.

Showing 20 of 25 references

Founder's Pitch

"Optimize on-device LLM efficiency using a Roofline analysis benchmarking framework."

BenchmarkingScore: 5View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

2/4 signals

5

Series A Potential

0/4 signals

0

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 2/12/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.