opensource.google.com

Menu

Introducing Three-Live: turning AI-generated Three.js into interactive 3D, AR, and WebXR across web and mobile

Tuesday, November 3, 2026

Want to add AI-generated 3D or XR to your web or mobile app? Unsure how to get started? That’s why we created the open source cross-platform project Three-Live—written entirely by Google Antigravity, in partnership with one former software engineer turned product manager. (Three-Live is not an officially supported Google product.)

You can think of Three-Live as a simple, unofficial companion to the more capable and feature-rich XR Blocks, Android XR’s web-based cross-platform framework for XR. The goal of Three-Live is to make it easy to get started with 3D and XR that’s AI-authored in Three.js. Three-Live combines the familiar developer experience of <model-viewer> and native mobile libraries with a sandboxed compiler for on-device or server-side compilation of untrusted LLM-generated JavaScript. Large language models (LLMs) have gotten remarkably good at writing software, and that includes generating 3D code in procedural Three.js JavaScript that describes objects, materials, lighting, and animations. But runtime AI-generated code is not trusted, and requires security sandboxing for safe execution. Also, mobile devices provide native support for 3D and XR rendering, and forcing them to run a webview limits the performance.

Screenshot of the Three-Live interactive studio running in a browser, showing live procedural Three.js controls and a real-time PBR 3D scene with metallic and emissive materials.

Today, we are excited to release Three-Live (v1.0.0, Developer Preview) under the Apache 2.0 license. It’s a lightweight, cross-platform open source library and on-device compiler that bridges the gap between AI-generated Three.js code and high-performance 3D, AR, and WebXR rendering across web, Android, and iOS.

Flowchart showing a procedural Three.js script entering the on-device Three-Live sandbox and compiling in milliseconds into binary glTF 2.0 (GLB) and USDZ for WebGL2/WebXR on the web, Google Filament and Scene Viewer on Android, and RealityKit and Quick Look on iOS.

How Three-Live works

Rather than use Three.js as a browser-only rendering loop, Three-Live treats a declarative subset of the Three.js API as a universal, portable scene description language:

Sandboxed execution with strict resource quotas: On the web, untrusted scripts execute inside an isolated Web Worker (with an optional opaque-origin sandboxed <iframe> tier) where network primitives (fetch, XMLHttpRequest, WebSocket, dynamic import()) are stripped before a single line of user code runs. On Android, iOS, macOS, and the command line, scripts execute inside an embedded Rust compiler powered by the Boa ECMAScript engine. Both runtimes enforce hard execution timeouts and geometry quotas (capping vertices, triangles, meshes, and procedural textures) so runaway scripts cannot freeze the host application.

Fast on-device compilation to GLB and USDZ: As the script constructs geometries, physically based rendering (PBR) materials, procedural canvas textures, hierarchy groups, and keyframe animations, Three-Live serializes the resulting scene graph directly into standard binary glTF 2.0 (.glb) and uncompressed Apple USDZ (.usdz) byte buffers in memory—typically in two to five milliseconds.

Platform-optimized rendering: Because the output is a standard binary 3D asset coupled with declarative animation bindings, each platform renders it using its built-in graphics pipeline:

  • Web (three-live and xr-live): A custom zero-dependency WebGL2 PBR renderer and <three-live> web component—inspired by <model-viewer>—complete with procedural Studio HDRI reflections, screen-space ambient occlusion (SSAO), bloom, shadow mapping, and a single-click AR handoff to Android Scene Viewer, Apple AR Quick Look, or immersive WebXR. At launch, the standard bundle with sandboxed scripting and AR is about 45 KB gzipped, and the xr-live spatial computing suite is about 55 KB.
  • Android (com.google.threelive:compiler): A Kotlin SDK and multi-architecture JNI library (arm64-v8a, armeabi-v7a, x86_64) that compiles Three.js strings on a background coroutine straight into ByteBuffer assets for Google Filament ModelViewer and Scene Viewer AR.
  • iOS and macOS (ThreeLiveCompiler): A Swift Package and five-slice XCFramework that compiles Three.js scripts on-device for RealityKit ModelEntity and ARQuickLookPreviewController.
Screenshot of the XR-Live Spatial Computing Playground demonstrating six-degrees-of-freedom (6DoF) spatial traits, live procedural Three.js source editing, and spatial DOM UI projection.

Declarative 3D and spatial WebXR in HTML

On the web, adding an interactive, AI-generated 3D model with built-in orbit controls and mobile AR support requires just a single HTML custom element:

<script src="https://cdn.jsdelivr.net/npm/three-live@1.0.0/dist/three-live.min.js"></script>
<three-live allow-client-scripts camera-controls ar shadow-intensity="1" environment-image="studio">
  <script type="text/three-live">
    const knot = new THREE.Mesh(
      new THREE.TorusKnotGeometry(0.6, 0.2, 128, 32),
      new THREE.MeshStandardMaterial({
        color: 0x4285f4,
        metalness: 0.85,
        roughness: 0.15
      })
    );
    scene.add(knot);
    // Baked into a looping glTF animation (4 seconds by default).
    scene.userData.animate = (t) => {
      knot.rotation.y = t * (Math.PI / 2);
    };
  </script>
</three-live>

The script runs in the sandbox described above. Because inline scripts are client-modifiable, they require the explicit allow-client-scripts opt-in; server-generated scripts can be loaded with script-src instead.

Only need to display existing models? The viewer-only build drops the script compiler and AR handoff and weighs about 23 KB gzipped at launch—tiny compared to the full Three.js library. The Three-Live viewer focuses on fast-loading PBR display, orbit controls, and glTF animation:

<script src="https://cdn.jsdelivr.net/npm/three-live@1.0.0/dist/three-live-viewer.min.js"></script>
<three-live src="chair.glb" camera-controls auto-rotate></three-live>

For spatial computing headsets and mobile AR browsers, the companion xr-live package adds <xr-live> and <xr-scene>, enabling six-degrees-of-freedom (6DoF) hand-tracking gestures (pinch, grab, two-hand scale), spatial DOM projection, and real-time voice- or text-to-3D object synthesis inside an active WebXR session.

Try it today

We built Three-Live to make 3D and spatial computing accessible to web, mobile, and AI developer communities without requiring complex 3D modeling pipelines. You can explore the project and try it right in your browser:

Three-Live is currently in Developer Preview, and we welcome feedback, bug reports, and pull requests from open source developer communities on GitHub.

This Week in Open Source for October 30, 2026

Friday, October 30, 2026

Light-theme Google Open Source banner reading 'This Week in Open Source' above four connected circular icon medallions representing upcoming events (calendar), open source reads (globe), code and tutorials (laptop with code brackets), and community (people).

A look around the world of open source

Right before Halloween weekend, it feels fitting to ask what actually haunts open source communities right now—from supply-chain ghosts lurking in commit histories and the hidden cost of maintaining isolated "zombie" forks to models wearing open source costumes without sharing what is under the mask. Across this week's reads, maintainers, researchers, and engineers share how they are keeping the lights on: setting clear community boundaries for AI contributions, wiring human sign-off and cost guardrails directly into automated workflows, and co-building open infrastructure across hardware stacks. Technology only serves people when the humans doing the work stay in control of the machinery—and transparent, inspectable tools remain our best defense against things that go bump in the night.

Upcoming events

🗓️ November 2026

  • Open Source in Finance Forum (OSFF) New York (November 4–5, 2026) – New York, New York, USA. Dedicated industry conference examining open source compliance, supply-chain security, and collaborative innovation across regulated financial institutions.
  • SeaGL (Seattle GNU/Linux Conference) 2026 (November 6–7, 2026) – Seattle, Washington, USA & Virtual. Free, grassroots technical summit dedicated to spreading awareness and knowledge of free and open source software, hardware, and culture.
  • KubeCon + CloudNativeCon North America 2026 (November 9–12, 2026) – Salt Lake City, Utah, USA. The Cloud Native Computing Foundation's (CNCF) flagship conference uniting adopters and maintainers around Kubernetes and containerized distributed infrastructure—featuring over 35 sessions and keynotes from Googlers including Abdel Sghiouar, Jago Macleod, Tim Hockin, Kaslin Fields, John Belamaric, Dawn Chen, Janet Kuo, Benjamin Elder, Antonio Ojea, Lior Lieberman, Michelle Au, and Braydon Kains across Kubernetes Special Interest Groups (SIGs), etcd, containerd, Gateway API, Common Expression Language (CEL) admission policies, and agent sandboxes, plus the Google-sponsored Community Hub.
  • SFSCON (South Tyrol Free Software Conference) 2026 (November 13–14, 2026) – Bolzano, Italy. One of Europe's longest-running free software conferences bringing together public-sector decision-makers and developers to advance digital sovereignty and open infrastructure.

🗓️ December 2026

  • Yocto Project Virtual Summit 2026.12 (December 1–3, 2026) – Virtual. Community summit for embedded Linux engineers and maintainers building custom, reproducible Linux distributions across edge and Internet of Things (IoT) hardware.
  • Open Source Summit Japan 2026 (December 7–9, 2026) – Tokyo, Japan. The Linux Foundation's premier Asia-Pacific conference connecting open source developers, kernel maintainers, and enterprise leaders across cloud, embedded Linux, and open AI—featuring a keynote by Google's Kaz Sato on building agents on open standards alongside sessions from Googlers Tanya Sharma, Tarun Sahu, and Anurag Sinha.
  • Open Compliance Summit 2026 (December 10–11, 2026) – Tokyo, Japan. Specialized gathering uniting legal, security, and Open Source Programs Office (OSPO) practitioners around OpenChain, Software Package Data Exchange (SPDX), software bills of materials (SBOMs), and global open source supply-chain compliance.

🗓️ January 2027

  • Free and Open Source Software Developers' European Meeting (FOSDEM) 2027 (January 30–31, 2027) – Brussels, Belgium. Europe's largest free, volunteer-organized gathering for free and open source software developers at the Université libre de Bruxelles—with calls for participation now open across 77 community developer rooms and main-track proposals open through November 16.

Open calls for proposals (CFPs)

  • Free and Open Source Software Developers' European Meeting (FOSDEM) 2027 (Event: January 30–31, 2027 – Brussels, Belgium) – Main-track CFP deadline: November 16, 2026 (developer room calls for participation open across 77 accepted community developer rooms, with devroom schedules published by December 7, 2026).
  • AtmosphereConf 2027 (Event: April 29 – May 2, 2027 – Amsterdam, The Netherlands) – Round 1 CFP deadline: November 30, 2026 (Round 2: January 11 – February 14, 2027). Community conference uniting developers, researchers, and creators building on the Authenticated Transfer Protocol (AT Protocol), open social web standards, and decentralized agent substrates across Build, Create, Inform, and Govern tracks.

Open source reads and links

Which of these stories will you be chatting about at your next meetup or conference? Let us know! Share with us on our @GoogleOSS X account or our @opensource.google Bluesky account.

This Week in Open Source for October 23, 2026

Friday, October 23, 2026

Light-theme Google Open Source banner reading 'This Week in Open Source' above four connected circular icon medallions representing upcoming events (calendar), open source reads (globe), code and tutorials (laptop with code brackets), and community (people).

A look around the world of open source

What actually sustains an open source community when the cost of generating code drops toward zero, while the human labor required to review, govern, and secure it stays just as demanding? Across this week's reads, researchers, legal scholars, and builders examine the tension between automated volume and human stewardship—from public-infrastructure policy and maintainer bandwidth to provenance transparency, copyright law, and compact models running entirely on local hardware. Because software only serves people when human judgment remains in the loop, protecting maintainer agency and keeping project doors open to real newcomers matter more than ever.

Upcoming Events

🗓️ October 2026

  • Open Source AI Week 2026 (October 19–24, 2026) — San Francisco Bay Area, California, USA. Now in its final stretch across the Bay Area alongside PyTorch Conference, this decentralized week of community meetups, workshops, and hackathons—with Google DeepMind and Gemma as Platinum Sponsor—wraps up this weekend with tonight's Open Source AI Awards Night (Friday, October 23, 5:00–10:00 PM PT at Fort Mason, San Francisco) and tomorrow's Google Gemma Hardware Hackathon at AGI House (Saturday, October 24, 10:00 AM–5:00 PM PT in Hillsborough, CA).
  • AGNTCon + MCPCon North America 2026 (October 22–23, 2026) — San Jose, California, USA. Happening this week, this Linux Foundation and Agentic AI Foundation (AAIF) conference focuses on building and scaling production agentic systems with open standards—featuring keynotes by Google's Rao Surapaneni, Sarah Drasner, and Chi Wang, plus sessions from Googlers Vishal Motwani & Alan Blount (on Agent-to-User Interface [A2UI]), Junjie Bu (on interoperable agent discovery), Amit Handa (on agentic commerce), Dominic Farolino (on Model Context Protocol [MCP] Apps + WebMCP), and Prerna Kakkar & Kurtis Van Gent (on EvalBench).
  • GitHub Universe 2026 (October 28–29, 2026) — San Francisco, California, USA & Virtual. Annual global developer gathering highlighting open source workflows, collaborative security, and multi-model AI-assisted software engineering.

🗓️ November 2026

  • Open Source in Finance Forum (OSFF) New York (November 4–5, 2026) — New York, New York, USA. Dedicated industry conference examining open source compliance, supply-chain security, and collaborative innovation across regulated financial institutions.
  • SeaGL (Seattle GNU/Linux Conference) 2026 (November 6–7, 2026) — Seattle, Washington, USA & Virtual. Free, grassroots technical summit dedicated to spreading awareness and knowledge of free and open source software, hardware, and culture.
  • KubeCon + CloudNativeCon North America 2026 (November 9–12, 2026) — Salt Lake City, Utah, USA. The Cloud Native Computing Foundation's (CNCF) flagship conference uniting adopters and maintainers around Kubernetes and cloud-native infrastructure—featuring over 35 sessions and keynotes from Googlers including Abdel Sghiouar, Jago Macleod, Tim Hockin, Kaslin Fields, John Belamaric, Dawn Chen, Janet Kuo, Benjamin Elder, Antonio Ojea, Lior Lieberman, Michelle Au, and Braydon Kains across Kubernetes Special Interest Groups (SIGs), etcd, containerd, Gateway API, Common Expression Language (CEL) admission policies, and agent sandboxes, plus the Google-sponsored Community Hub.
  • SFSCON (South Tyrol Free Software Conference) 2026 (November 13–14, 2026) — Bolzano, Italy. One of Europe's longest-running Free Software conferences bringing together public-sector decision-makers and developers to advance digital sovereignty and open infrastructure.

🗓️ December 2026

  • Yocto Project Virtual Summit 2026.12 (December 1–3, 2026) — Virtual. Community summit for embedded Linux engineers and maintainers building custom, reproducible Linux distributions across edge and Internet of Things (IoT) hardware.
  • Open Source Summit Japan 2026 (December 7–9, 2026) — Tokyo, Japan. The Linux Foundation's premier Asia-Pacific conference connecting open source developers, kernel maintainers, and enterprise leaders across cloud, embedded Linux, and open AI, including sessions from Google engineers such as Anurag Sinha.
  • Open Compliance Summit 2026 (December 10–11, 2026) — Tokyo, Japan. Specialized gathering uniting legal, security, and Open Source Programs Office (OSPO) practitioners around OpenChain, Software Package Data Exchange (SPDX), software bills of materials (SBOMs), and global open source supply-chain compliance.

Open Source Reads and Links

  • [Blog] Open Enables a Lot: The OSI at UNGA81 — At the 81st United Nations General Assembly (UNGA81), the Open Source Initiative (OSI) hosted a panel featuring Google OSPO’s Amanda Casari alongside policy and academic leaders to explore how open source reshapes public infrastructure. Framed by Duane O’Brien’s takeaway that “open by itself does very little, but enables a lot,” what shared scaffolding is needed to turn open licenses into real public value?
  • [Paper] “AI Slop is DDoSing Open Source”: Understanding the Impact of AI-Generated Contributions on Open Source Sustainability — After hearing questions about AI-generated pull requests online and at conferences for a while now, I came to Google and Oregon State University’s study of 294 repositories looking for what solutions are actually working. Surveying 11 remediation strategies as first-time contributor merge rates drop 18.18%, how can communities filter synthetic noise without closing the door on newcomers?
  • [Article] Who’s Writing Open Source Code? — Have AI coding agents actually taken over open source repositories, or is human authorship still the norm? Auditing 24,000 commits across 15 critical C infrastructure projects from the first half of 2026, RedMonk’s Stephen O’Grady finds that fewer than 1% carry explicit machine co-author or agent markers—raising a pressing question: how should open source communities build cultural norms around provenance transparency?
  • [Article] The copyright problem with AI-generated code — In creative circles online, people often argue that prompting AI makes you closer to an art patron or a music producer than the artist—but I had never thought about the copyright realities for software. Since open source licenses rely on human copyright, FreeDOS founder Jim Hall asks a foundational question: can you even license code you didn’t actually author?
  • [Blog] Launching an opt-in vulnerability-finding service for open-source software — Inspired by Google’s OSS-Fuzz, Anthropic’s new opt-in OSS Scanner offers open source maintainers free, periodic security audits complete with test reproducers and suggested patches running in isolated Docker environments. Giving resource-constrained projects direct access to frontier vulnerability detection is a welcome step forward—how can we keep expanding shared security tooling to help upstream maintainers catch complex bugs early?
  • [Blog] Do Agent Skills Help? I Ran 72 Trials to Find Out — Evaluating whether AI agent skills beat prompt-and-guess baselines, Karl Weinmeister ran 72 sandboxed trials across 12 scenarios using Harbor and SkillEvaluator—complementing Google’s open source skill-reach suite for catching description collisions across harnesses like AAIF’s Goose and Claude Code. Together, they raise a practical question for maintainers: how do we test both skill discovery and execution quality?
  • [Blog] Make the PDS Your Own: Customization and Metrics — The Authenticated Transfer Protocol (AT Protocol) is one of my major interests right now, so seeing how people are making its foundations work in practice is fascinating. The latest Reference Personal Data Server (PDS) release adds custom OAuth login branding, 300MB video blobs, and direct-to-Prometheus OpenTelemetry metrics in under 1GB of RAM—what other operational building blocks will help small teams self-host federated infrastructure?
  • [Article] Google’s new 4B Gemma model cuts speaker-labelling errors on all four benchmarks, two barely — Automated transcripts still struggle when speakers talk over one another in meetings and interviews. Built on Google’s Gemma 4 E4B and open source DiarizationLM framework, the community-trained Apache 2.0 DiarizationLM-Gemma-4-E4B-v1 approaches speaker diarization as a lightweight post-processing pass over existing transcripts—beating an 8B Llama 3 baseline at half the size. Where can compact local models clean up brittle pipeline handoffs in your own workflows?
  • [Blog] Open-Source Voice AI runs entirely on ESP32-S3 — Some of the most inspiring moments in open source come from individual builders experimenting at the edges of hardware constraints. Anankush Pandit’s GNU General Public License (GPL) Ivy AI packs wake-word detection, speech recognition, a 4-bit language model, and speech synthesis onto an ESP32-S3 microcontroller with just 8MB of pseudo-static RAM (PSRAM)—making us wonder what other everyday devices could run entirely offline?

Which of these stories will you be chatting about at your next meetup or conference? Let us know! Share with us on our @GoogleOSS X account or our @opensource.google Bluesky account.

Introducing the Elephant-Goldfish Model plugin: scaling design-driven AI software development

Thursday, October 22, 2026

Official logo of the Elephant-Goldfish Model: a minimalist split mark featuring an elephant profile in blue and a goldfish profile in orange.

Shifting left in the AI coding era

AI-powered velocity is transformative; however, it has silently introduced a potential reliability crisis by also increasing the velocity of “slop,” bugs, and session context collapse. Generative AI tools excel at increasing coding speed, but pure speed without structured guardrails means we are often auto-scaling our mistakes rather than simply writing code faster. We need a paradigm shift, aligning the human need for system comprehension with AI’s capacity for execution.

As co-author Dave Rensin outlines in the article Elephants, Goldfish, and the New Golden Age of Software Engineering, “Design is the new code.”

Understanding the Elephant-Goldfish Model (EGM)

The EGM framework is a metaphor for a powerful way to develop AI-assisted software quickly and safely with humans intentionally in the loop.

The “Elephant” is a context-rich, long-horizon AI session that holds the end-to-end architectural vision and project memory. No code is written here; it is purely dedicated to design, intent, and capturing micro-decisions. The Elephant session is where the AI interviews you and you debate the merits of your choices.

Conversely, “Goldfish” are stateless, zero-context sessions used strictly to validate specifications. Because they share no “blind spots” with the designer, they act as objective critics, probing for gaps and edge cases.

The goal of this method is for the AI to correctly produce the code you wanted the first time after you press Enter.

Announcing the open source Elephant-Goldfish Model plugin

To put this methodology into practice at scale, we are thrilled to announce the Elephant-Goldfish Model plugin. Originally, this plugin was developed internally for Google software engineers, and is now open source. Thousands of Googlers use this plugin every day to ship production Google code. Released under the Apache 2.0 license, the repository provides everything you need to implement this framework. Developers will find customizable Markdown rules, defined subagent personas, and structured review workflows ready to integrate into your own environments.

The plugin’s core goal is to bring the EGM framework directly into Antigravity, with other development environments upcoming. It automates the orchestration of the EGM lifecycle: managing context transfer between Elephants and Goldfish, facilitating validation loops, and rendering design documents, shifting the developer’s role from micromanager to executive reviewer.

The EGM plugin in a nutshell

EGM lifecycle workflow diagram illustrating the three phases: Phase 1 Brainstorm (Growing the Elephant), Phase 2 Draft (Drafting with the Elephant), and Phase 3 Review (The Goldfish Protocol with Comprehension Check, Hostile Critic, and Implementation Readiness validators).

The EGM lifecycle, automated with the plugin, walks the user through three co-design phases:

Phase 1: Growing the Elephant (egm-brainstorm)

Developers load the system context and adhere to a “No Code” rule to co-design features, debate trade-offs, and challenge assumptions.

Phase 2: Drafting with the Elephant (egm-draft)

Developers iteratively draft a Markdown design document that covers the problem definition, technical plan, alternatives considered, and a detailed implementation plan that enumerates the specific files to change.

Phase 3: The Goldfish Protocol (egm-review)

The Goldfish Protocol shifts the model from co-design to adversarial validation, using stateless AI instances to probe the design for weaknesses. The plugin automates a three-step validation sequence:

  • Comprehension Check: A stateless Goldfish reads the complete design document and must explain the architecture and intent back to the Elephant. If the Goldfish cannot accurately summarize the plan, it indicates the document is ambiguous and requires further drafting.
  • Antagonistic Review: Multiple Goldfish instances assume the role of skeptical, antagonistic technical reviewers. They are tasked with identifying potential edge cases, hidden dependencies, and logical gaps. Their critique is funneled back to the Elephant session for resolution.
  • Implementation Readiness Check: A final Goldfish performs a strict go/no-go check. It verifies that all necessary information—file paths, data structures, and function signatures—is present and unambiguous. This ensures the spec is ready for precise transcription into code.

Human judgment is the artifact

Ultimately, human judgment is the only artifact that truly matters in an AI-saturated world and we want to align the human need for system comprehension with AI’s capacity for execution. We hope this plugin will make it easier for developers of all skill levels to follow a process that more quickly and safely converts the idea they had in their head to a robust and well-built app on their screen.

We invite developers, architects, and AI enthusiasts to contribute to the plugin, customize its validation rules, and help define the future of collaborative software engineering.

To get started, check out the Elephant-Goldfish Model repository on GitHub.

Announcing the verifiable quantum circuit compilation competition on Kaggle

Wednesday, October 21, 2026

Light-theme Google Open Source banner featuring the Google Open Source logo above four connected circular icon medallions representing code and product launches, contributors and programs, open source journeys, and ecosystem stewardship.

While quantum computing holds the key to solving some of our most complex scientific challenges, current hardware is still limited by qubit counts and gate errors. Quantum error correction can overcome those errors, but it adds substantial overhead to every qubit and gate an algorithm uses. That makes circuit size one of the biggest factors in when a quantum algorithm becomes practical: every qubit and gate we remove lowers the bar that hardware must clear. To bring real-world quantum applications within reach sooner, it is critical to first compress the circuits that power them.

To help bridge this gap, the Google Quantum AI team is launching a competition on Kaggle challenging you to use AI to build smaller, more efficient quantum circuits. The competition is powered by kickmix, our new open source C++20 and Python library in Qualtran for efficiently building and testing large quantum circuits. Our companion paper, Leveraging verifiable structure in quantum circuits to find more efficient compilations with agentic AI, describes the approach in detail.

Turning compilation into an AI agent loop

In the past, optimizing quantum algorithms meant domain experts meticulously tuning circuits by hand and publishing incremental wins one paper at a time. Today, agentic AI can search for more efficient circuits automatically, but such results can only be trusted when candidate circuits can be efficiently verified for correctness. For arbitrary quantum circuits, classical verification is intractable because quantum gates create superpositions over exponentially many classical bitstrings. Fortunately, many of the most expensive subroutines in fault-tolerant algorithms can be built within a structured subclass of circuits, called “kickmix” circuits, which we introduced in our earlier work. Built from reversible classical logic, diagonal phase gates, and measurement-based uncomputation, kickmix circuits map each input bitstring to a single output bitstring and phase without creating new superpositions. A classical computer can therefore run randomized fuzz testing on bitstring inputs in linear time to establish the circuit’s approximate correctness on full quantum states with high confidence.

Randomized fuzz testing does not prove exact equivalence, but most quantum algorithms can tolerate a small, bounded error. In fact, using approximations can cut gate and qubit counts significantly. Finding such approximations by hand is tedious, making it a great task for AI agents. With kickmix in Qualtran, agents can build large circuits quickly and fuzz test them at 60 billion gates per second on a single CPU core.

How the competition works

The competition features three benchmarks, each targeting a major kickmix bottleneck in a useful quantum algorithm in order to call attention to the broad utility of this verification paradigm. For each benchmark, we provide a reference baseline circuit and a standalone verifier, both open source under the Apache 2.0 license. Your goal is to submit a circuit that passes the verifier while minimizing a cost score based on its qubit and gate counts:

  • Fusion energy: Designing inertial confinement fusion targets requires simulating how quickly charged particles slow down in a hot, dense plasma fuel (Proceedings of the National Academy of Sciences (PNAS)). The main bottleneck is computing the electric potential energy between every pair of particles, which is inversely proportional to their distance. The task is a quantum take on the classic fast inverse square root: given the squared distance x, apply a phase proportional to 1/√x, accurate to a tiny fraction of its exact value.
  • Optimization: Decoded Quantum Interferometry (Nature) is a quantum algorithm for solving hard combinatorial optimization problems. On one such problem, Optimal Polynomial Intersection (OPI), it finds better solutions than any known efficient classical algorithm. The main arithmetic bottleneck in solving OPI is decoding a Reed-Solomon code in superposition. The task is to build this decoder as a quantum circuit.
  • Chemistry: Fertilizer production depends on nitrogen fixation, which converts nitrogen gas from the air into ammonia. Industry does this at high temperature and pressure, using about 1–2% of the world’s energy supply, while bacteria do it at ambient conditions with the enzyme nitrogenase, whose active site is an iron-molybdenum cluster called FeMoCo. Understanding how FeMoCo works requires modeling its strongly correlated electrons, a long-standing target for quantum computers. Our recent algorithm (Physical Review X (PRX)) makes that quantum simulation cheaper by classically factorizing the molecule’s Hamiltonian into a compact sum of squares, so the quantum computer needs far fewer steps. At each step, the main bottleneck is a quantum lookup table that loads the parameters of that factorized Hamiltonian in superposition. The task is to co-design both parts: find an accurate factorization that needs fewer steps, and build compact circuits to load its parameters so each step costs less.

Get involved

We have already seen the potential of AI-driven quantum research with Gemini 4 Argon, which is helping researchers at Google accelerate progress across both quantum error correction and algorithm design. We’re excited that the broader research community is embracing this approach too, with simultaneous independent work pairing the kickmix paradigm with AI agents to reduce costs on related subroutines. However, our own internal runs with Gemini models show that all three benchmarks can be further improved beyond the circuits reported to date (and we’ve published a hash of those circuits in our recent manuscript to reveal after the competition), so the competition remains open and interesting.

Could we get more out of a quantum computer simply by asking it to do less? We invite you to help us answer that question.

Visit the competition page on Kaggle to read the full details, explore the resources, and submit your work.

.