fx vs Gemini Spark: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of fx and Gemini Spark — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

fx

Vercel Labs

Free

Vercel Labs' tiny open-source coding agent — a ~6 MB native CLI written in Zig, built for speed, embeddability and Unix-style ergonomics.

Tiny Native Binary: The whole agent ships as a roughly 6 MB executable designed for instant installation and for embedding in resource-constrained environments and agent sandboxes.
Instant Time to Prompt: fx cold starts in about 10 microseconds and performs no unnecessary work or I/O before accepting user input, which matters for programmatic invocation.
Minimal Memory Footprint: A single-digit-megabyte memory baseline lets you pack many concurrent instances onto one machine.
Shell-Like Ergonomics: Scroll history is preserved by default and output is deliberately sparse, so the CLI composes like a Unix tool instead of taking over the terminal.
Context Efficiency: A minimal system prompt and tool surface reduce token spend and improve time-to-first-token performance.
WebAssembly Builds: Optimal fx.wasm builds from the Zig toolchain shrink the binary further and make the network stack pluggable, enabling the in-browser demo.
Model and Provider Agnostic: Works with local models, LLM gateways, direct provider API access or existing subscriptions rather than locking you to one vendor.
Extensible Small Core: Capabilities are added through skills, plugins and MCPs, following a Unix-like philosophy of a small core with composable extensions.

Sandboxed Agent Execution: Ship a full coding agent inside a container or sandbox where a large runtime would not fit.
Embedding in Larger Systems: Use fx as the agent harness inside your own product or internal platform rather than building a loop from scratch.
CI and Scripted Automation: Invoke a coding agent from pipelines and scripts where fast cold starts and quiet output matter more than an interactive UI.
Agent Harness Research: Experiment with system prompt and tool design on a deliberately minimal, readable Apache-2.0 codebase.
Local-Model Coding: Run agentic coding against a locally hosted model without any dependency on a specific cloud provider.
Browser-Based Demos and Playgrounds: Compile to WebAssembly and run the agent client-side with networking delegated to browser fetch.

Google

Paid

Google's always-on personal AI agent that monitors your inbox, manages your schedule, and completes multi-step tasks 24/7.

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.

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.