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

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

Aside

Aside Computer Inc.

Freemium

A Chromium desktop browser with a built-in agent that signs in and completes real work across your logged-in sites.

Agentic Browsing: The agent operates your logged-in websites directly - clicking, typing and navigating - so tasks that need no public API still get done.
Local Memory: Browsing history is distilled into on-device memory files so the agent already knows which tools and accounts a recurring task involves.
Agent Password Manager: Credentials are autofilled into pages through hardware-backed encryption and Secure Enclave storage, never handed to the model.
Human Approval Gates: Sensitive steps such as payments, posts and outbound messages pause for your confirmation before the agent proceeds.
Access Audit Log: Every credential use and scoped permission grant is recorded so you can see exactly what the agent touched and when.
Routines: Scheduled recurring tasks, such as a 9am daily briefing, run on their own and drop results back into the browser.
Bring Your Own Model: Connect an existing ChatGPT or Claude subscription or your own API key rather than paying twice for inference.
Sandboxed Execution: Filesystem and network access are isolated with guardrails so agent runs cannot reach beyond what the task needs.

Operations Backfill: Push the same record update through several internal dashboards that have no shared API.
Recruiting Prep: Reopen a candidate profile viewed yesterday and assemble interview notes from the sites already visited.
Inbox and Comment Triage: Draft replies, follow-ups and comment responses across email and social accounts under review.
Daily Briefing: Schedule a routine that gathers overnight metrics and trending topics into one morning summary.
Sales Research: Work through prospect sites and CRM screens to collect context before an outreach sequence.
Spreadsheet and Document Work: Have the agent edit local files and web spreadsheets as part of a longer task.

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.