Gemini Spark vs Lumi: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Gemini Spark and Lumi — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
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Gemini Spark
Google's always-on personal AI agent that monitors your inbox, manages your schedule, and completes multi-step tasks 24/7.
Key features
- Always-On Operation: Runs continuously on Google Cloud and keeps working even when your laptop is closed.
- Proactive Gmail Management: Organizes emails, drafts responses, prioritizes messages, and summarizes inbox activity.
- Calendar & Scheduling: Manages appointments, suggests scheduling improvements, and prepares meeting summaries.
- Google Workspace Integration: Connects natively with Gmail, Calendar, Drive, Docs, Sheets, Slides, YouTube, and Maps.
- Third-Party Connections: Links to apps like Canva, OpenTable, and Instacart, with more partners coming.
- Multi-Step Task Automation: Completes interconnected, recurring tasks such as spotting hidden fees or drafting reports from meeting notes.
- User-Controlled & Opt-In: You decide whether to enable it and which apps it can access.
Best for
- Inbox Triage: Automatically organize, prioritize, and draft replies to keep email under control.
- Schedule Management: Keep a calendar organized with proactive appointment and meeting prep.
- Recurring Monitoring: Set it to watch for things like hidden fees in monthly bills.
- Report Generation: Turn meeting notes from chats and emails into polished Google Docs reports.
Lumi
A Google PAIR prototype that adds AI-powered annotations, granular summaries, and custom Q&A to arXiv research papers.
Key features
- Granular Summaries: Generates summaries at multiple granularities (section- or paragraph-level) to surface key ideas and make long papers easier to skim and comprehend.
- Inline Annotations: Attaches contextual, sentence- or paragraph-specific annotations directly onto the paper text to explain terminology, methods, or results in place.
- Custom Q&A: Lets users ask targeted questions about a paper and receive context-aware answers derived from the document content to clarify methods, results, or motivations.
- arXiv Integration: Built specifically to work with arXiv papers, enabling quick access to preprints and their metadata while preserving original paper structure.
- Open-Source Prototype: Source code available under an Apache-2.0 license on GitHub, allowing inspection, reuse, and community-driven improvements.
- Research Navigation Aids: Provides tools to jump between sections, references, and highlighted insights to streamline literature review workflows.
- Contextual Highlighting: Highlights important sentences and phrases based on AI analysis to draw attention to key contributions and claims.
- Collaboration-Friendly Outputs: Produces shareable annotations and summaries that can be used to coordinate reading lists and group discussions.