✳flâneur — a map of the web's best reading

[2605.17172] OpenJarvis: Personal AI, On Personal Devices

arxiv.org · 757 words · saved by 1 readers

Abstract:Personal AI stacks, like OpenClaw and Hermes Agent, are becoming central to daily work, yet they route nearly every query (often over sensitive local data) to cloud-hosted frontier models. Replacing frontier models with local models inside existing stacks does not work: swapping Claude Opus 4.6 for Qwen3.5-9B drops accuracy by 25-39 pp across personal AI tasks like PinchBench and GAIA. Existing stacks bundle agentic prompts, tool descriptions, memory configuration, and runtime settings around a specific cloud model. Only the prompts can be tuned, and state-of-the-art prompt optimizers close just 5 pp of the local-cloud gap on their own. This motivates a decomposed personal AI stack: one that exposes individual primitives which can be optimized individually or jointly to close the local-cloud gap. We present OpenJarvis, an architecture that represents a personal AI system as a typed spec over five primitives: Intelligence, Engine, Agents, Tools & Memory, and Learning. Each primitive is an independently editable field, making the stack end-to-end optimizable and measurable against accuracy, cost, and latency. Towards closing the local-cloud gap without surrendering local-model properties, OpenJarvis introduces LLM-guided spec search, a local-cloud collaboration in which frontier cloud models propose edits across the spec at search time, only non-regressing edits are accepted, and the resulting spec runs entirely on-device at inference time. With LLM-guided spec search, on-device specs match or exceed cloud accuracy on 4 of 8 benchmarks and land within 3.2 pp of the best cloud baseline on average. They also reduce marginal API cost by ~800x and end-to-end latency by 4x.

[2605.17172] OpenJarvis: Personal AI, On Personal Devices --> Computer Science > Machine Learning arXiv:2605.17172 (cs) [Submitted on 16 May 2026] Title: OpenJarvis: Personal AI, On Personal Devices Authors: Jon Saad-Falcon , Avanika Narayan , Robby Manihani , Tanvir Bhathal , Herumb Shandilya , Hakki Orhun Akengin , Gabriel Bo , Andrew Park , Matthew Hart , Caia Costello , Chuan Li , Christopher Ré , Azalia Mirhoseini View a PDF of the paper titled OpenJarvis: Personal AI, On Personal Devices, by Jon Saad-Falcon and 12 other authors View PDF HTML (experimental) Abstract: Personal AI stacks, l

Explore this link on the map →

saved by

related reading