Labvanced vs Pavlovia
Part of Labvanced's platform comparisons.
Labvanced and Pavlovia serve researchers from different starting points. Pavlovia is Open Science Tools' online hosting layer, most commonly used by PsychoPy researchers, letting researchers with an existing Python-based paradigm run it with remote participants. Labvanced is a no-code platform built for the browser from the start, with peer-reviewed webcam eye tracking, emotion detection, remote heart rate measurement, embedded speech-to-text transcription, AI-based translation into 50 languages, and an AI assistant for experiment building all built in natively. Both can collect data from remote participants online. Only one does it without writing code, and without splitting a study across two separate tools when a lab needs both in-lab hardware integration and online deployment.
Table of Contents
At a Glance
| Capability | Pavlovia (PsychoPy) | Labvanced |
|---|---|---|
| No-code visual builder | Partial: the Builder GUI generates a Python script for desktop use, with a separate JavaScript (PsychoJS) version created for online use; designs beyond simple paradigms can require direct editing of either | Yes: full no-code builder, no scripting required for standard or complex designs |
| Online deployment | Requires exporting or syncing the Python experiment to PsychoJS (JavaScript) before it can run in a browser | Yes: built browser-native; no export step or translation layer required |
| Webcam eye tracking (online studies) | Possible via WebGazer.js, an officially documented PsychoPy/Pavlovia integration requiring custom code (not the no-code Builder) | Yes: native, peer-reviewed webcam eye tracking (Kaduk et al., 2024, Behavior Research Methods). No custom code required |
| Emotion detection (online studies) | Possible only as a custom third-party integration (Face API), documented as an advanced/custom-code technique rather than a no-code Builder feature; not independently validated for emotion classification | Yes: emotion detection above 90% accuracy averaged across emotions (varies by individual emotion) |
| Remote heart rate / rPPG (online studies) | No | Yes: expected within 1–3% of actual heart rate (validation against gold-standard devices ongoing) |
| Eye tracking / EEG hardware integration (in-lab) | Yes, via PsychoPy's desktop application (Tobii, SR Research EyeLink, and other trackers via ioHub; EEG triggering via parallel port or LabJack); not available through Pavlovia's online studies | Yes: via the Labvanced desktop app, with EEG/Lab Streaming Layer (LSL) integration, using the same visual builder as the online version |
| Multi-user / group studies | Possible via the Shelf (documented, code-based); not native/no-code and not equivalent to real-time infrastructure | Yes: up to 20 players, WebSocket-based infrastructure with lobby management, role assignment, and group formation |
| Mobile access | Browser-accessible on mobile devices; no native app, no offline mode | Yes: native iOS/Android apps with full offline data collection |
| Version control and collaboration | Yes: full Git/GitLab-based version history, issue tracking, and forkable experiments for lab groups | Shared study editing with permission-based collaborator access; no git-style version history |
| Pricing model | Per-participant credits (£0.24/credit), or a £1,800/year site license (50% reduction for institutions in emerging economies) | Flat, tier-based subscription across individual, lab, teaching, campus, and commercial license categories; not billed per participant |
Where Pavlovia Is Strong
PsychoPy has a substantial academic footprint: the original platform paper (Peirce, 2007, Journal of Neuroscience Methods) has over 4,900 citations (OpenAlex, accessed 2026-07-17), and PsychoPy publishes live monthly usage statistics at usage.psychopy.org. Pavlovia itself is maintained by Open Science Tools Ltd., closely tied to the University of Nottingham, where PsychoPy's creator and core development team are based.
Its timing precision is independently verified, not just self-reported. The timing mega-study (Bridges et al., 2020, PeerJ) found PsychoPy/PsychoJS to achieve close to millisecond precision on several browser and operating system combinations, though the authors themselves noted this represented "something approaching a best-case scenario" and recommended testing timing on the specific hardware a study will actually use.
Pavlovia's GitLab-based project structure is a genuine reproducibility asset: every experiment gets full version history, issue tracking, and the ability to fork a lab's canonical experiment for adaptation by other members, all under a shared namespace. For labs that value an auditable change history on their experiment code, this is real infrastructure.
For researchers who already have a working PsychoPy paradigm, the Builder's one-click sync to Pavlovia removes a real barrier, and free pilot credits mean testing a study costs nothing up front. PsychoPy's desktop application also has mature, well-documented integration with hardware eye trackers and EEG systems for in-lab research, developed and refined since 2002.
Where Labvanced Differs
Standard study creation in Labvanced does not require writing any code. PsychoPy's Builder generates Python underneath its visual interface, and PsychoPy's own documentation acknowledges that its browser-hosted engine, PsychoJS, has existed only since 2016 and is maintained by a much smaller team than the Python desktop version; components can "behave differently online or have rough edges" as a result (PsychoPy, "Caveats and cautions," psychopy.org/online/cautions.html).
That gap also shapes deployment. A PsychoPy user who wants both a hardware-integrated lab version and an online version of the same study works across two separate tools, PsychoPy desktop and Pavlovia, connected by an export-and-upload step. Labvanced's webcam eye tracking, emotion detection, and remote heart rate all run natively inside the same online study a participant is already taking. There is no separate authoring workflow to maintain: the same visual builder is used whether the study runs online or through the desktop app for in-lab hardware integration, with no export step connecting them.
The two platforms also part ways on group studies: Pavlovia's Shelf mechanism can share data between participants through custom code, but PsychoPy's own documentation states this can take up to 60 seconds to propagate an update from one participant to another, with no built-in matchmaking or session management. Labvanced provides native, real-time multi-user infrastructure instead of requiring researchers to build that coordination themselves. And where Pavlovia charges per participant credit, or requires a flat annual site license regardless of study volume, Labvanced's tier-based subscriptions make cost predictable without a per-session meter running, so the relative cost advantage grows as a study's sample size increases.
For UX and web-based research, Labvanced's Web Bridge Chrome extension lets researchers track eye movements, clicks, and scroll behavior directly on a live, external website inside a controlled study session.
Choose Which Fits Your Study
If you already have a working PsychoPy paradigm, are comfortable in Python, and your study doesn't need webcam-based physiological measurement or multi-user support online, Pavlovia is a clean fit. Its citation depth, GitLab-based version control, and independently verified timing are real strengths, and rebuilding a working paradigm elsewhere has a real cost.
Labvanced's advantage grows as studies move beyond a traditional single-participant PsychoPy workflow. Webcam eye tracking, emotion detection, remote heart-rate measurement, and multi-participant studies can all be built directly within Labvanced's visual interface, whereas comparable functionality in Pavlovia often depends on custom Python or JavaScript, third-party libraries, or additional infrastructure. That difference becomes more noticeable as studies grow more sophisticated: Labvanced lets researchers extend their experiments while staying within the same no-code workflow. Built by a team of PhD researchers, the platform reflects how studies are conducted in practice while keeping coding optional.
Migration Note
Researchers moving an existing PsychoPy/Pavlovia study to Labvanced will typically recreate it using Labvanced's visual builder. While this involves rebuilding the study rather than importing it directly, it also provides an opportunity to consolidate separate desktop and online workflows into a single platform. For researchers or labs moving existing paradigms, Labvanced also offers the study building service that can assist with rebuilding experiments.
FAQ
Last Reviewed
Last reviewed: 2026-07-17
Competitor features, pricing, and platform capabilities on this page were verified against Pavlovia's and PsychoPy's official documentation and pricing pages as of this date. Peer-reviewed research citations are referenced inline throughout.