Since Google announced the Chromium project in 2008, we have been excited to build on the great foundations of open-source web browsers and contribute to the continued development of a rich web platform. Today, Chromium is used by hundreds of different projects globally, including big browsers like Chrome, home electronics from LG, application frameworks like Electron and even custom applications like Bloomberg terminals and SpaceX capsule control software.
In 2024, Google made over 100,000 commits to Chromium, accounting for ~94 percent of contributions. While we have no intention of reducing this investment, we continue to welcome others stepping up to invest more.
Google also continues to invest heavily in the shared infrastructure of the Open Source project to "keep the lights on", including having thousands of servers endlessly running millions of tests, responding to hundreds of incoming bugs per day, ensuring the important ones get fixed, and constantly investing in code health to keep the whole project maintainable. This work represents hundreds of millions of US dollars in annual investment just for maintenance costs before any new feature, innovation or other business priorities can be addressed.
Sustainable funding of critical open source infrastructure remains a hot industry-wide topic of discussion and over the years we’ve heard from many companies and developers about how critical the Chromium project is to their work. They’ve also shared how they would like to support the continued health of the project, beyond direct engineering support.
Today Google is pleased to announce our partnership with The Linux Foundation and the launch of the Supporters of Chromium-based Browsers. The goal of this initiative is to foster a sustainable environment of open-source contributions towards the health of the Chromium ecosystem and financially support a community of developers who want to contribute to the project, encouraging widespread support and continued technological progress for Chromium embedders.
The Supporters of Chromium-based Browsers fund will be managed by the Linux Foundation, following their long established practices for open governance, prioritizing transparency, inclusivity, and community-driven development. We’re thrilled to have Meta, Microsoft, and Opera on-board as the initial members to pledge their support.
We welcome this additional investment into Chromium’s commons and we’re looking forward to working with the other members of the Supporters of Chromium-based Browsers to ensure that it meets the needs of the wider Chromium community. At the same time, we remain committed to being the responsible steward of the Chromium project and to the massive investment necessary to keep Chromium working well for the entire web industry.
In October 2020, Chrome enabled HTTP/3 by default. HTTP/3 (RFC 9114) runs over IETF QUIC (RFC9000). Default-enabling HTTP/3 in Chrome resulted in improved performance compared not only HTTP/1 and HTTP/2, but also Google QUIC. Benefits included reduced Google search latency and fewer rebuffers for YouTube.
The journey to optimizing performance did not end when HTTP/3 was default enabled. Recent advancements include the implementation of the HTTP/3 ORIGIN frame (RFC 9412) and Server's Preferred Address (RFC 9000 Section 9.6). The former enhances connection coalescing, while the latter reduces a connection's round trip time (RTT). Both features have been enabled by default in M131, which was released to Stable on 11/19.
When a connection is established for a specific hostname, the server’s certificate typically contains numerous other hostnames for which the server is authoritative. However, a client cannot immediately send requests for those other hostnames on that connection without first performing a DNS lookup for the other hostname and verifying that the IP address of the connection matches the resolved address. This additional DNS resolution introduces latency and significantly reduces the likelihood of connection pooling due to potential IP mismatches. The metrics from Chrome indicate that nearly 20% of HTTP/3 connections would be unnecessary if not for this IP mismatch.
Creating a new connection, even with QUIC 0-RTT, is expensive in terms of latency, memory, and CPU usage. This is because:
Additionally, features like HTTP priorities (RFC 9218) are only effective if there are multiple simultaneous responses to send.
The HTTP/3 ORIGIN Frame (RFC 9412) enables a server to indicate what domains it would like to pool onto a connection. Additionally, once the frame is received, it indicates other domains should not be pooled onto that connection, even if they are in the certificate.
In some cases, the initial server address to which the client connects is not the most efficient route. It might be behind an L4 load balancer, and connecting directly could increase stability. Particularly when using Anycast, it’s possible the server is distant from where traffic enters the network, creating a 3-legged path that increases the round trip time.
Once the handshake is confirmed, Server’s Preferred Address allows a server to indicate it would like the client to migrate to a different server IP. Though a QUIC connection is not bound to a single 4-tuple like TCP, this is the only type of migration in RFC9000 where the server can change its address.
So far, only Google’s Media CDN has widely enabled advertising an alternative address, but we expect more servers to adopt it soon. Testing has shown that this migration is successful over 99% of the time in Chrome and reduces average RTT by 40-80%.
Today’s The Fast and the Curious post covers how Chrome achieved best-in-class Speedometer scores on mobile devices, resulting in faster and smoother web experiences for Android users.
Chrome has always been about speed. Whether it's loading pages quickly, running complex web apps smoothly, or delivering a seamless browsing experience, performance is at the heart of our browser. And we're always looking for ways to make Chrome even faster.
Over the last two years, we have been hard at work on a number of performance improvements for Android devices. We're excited to share some of the progress we've made.
One of the key metrics we use to track Chrome's performance is the Speedometer benchmark. This benchmark is developed in collaboration with other major web browser engines and measures how quickly Chrome can complete interactions with web pages, including parsing/rendering HTML or CSS and running JavaScript.
Since the release of Chrome M112, we've seen a significant increase in Speedometer 2.1 scores on Android devices [1]. In fact, on many devices, scores more than doubled, with the newest Snapdragon® 8 Elite Mobile Platform setting new records for Speedometer performance on mobile devices! These huge accomplishments are a testament to the work not only of the Chrome and Android teams, but also our silicon and SoC partners.
Since Chrome M112, Speedometer 2.1 scores have more than doubled on many Android devices. [1]
The improvements resulted from several changes, including:
Let's take a closer look at each of these areas.
The Android device ecosystem is very diverse. From entry-level phones to the newest premium ones, Chrome needs to run well on all devices. Up until last year, we shipped the same Chrome build to all these different Android devices. The memory and disk size constraints on entry-level devices resulted in Chrome having to prioritize a small binary size. Consequently, many modern build optimizations were out of reach, as they resulted in much larger binaries.
With M113, Chrome was finally able to ship a separate higher-performance build targeting premium Android devices via the Google Play Store. While we still ship a more binary-size-constrained build to other devices, this approach allowed us to land some of those modern optimizations into the new premium build:
Together, these build optimizations account for more than half of the overall Speedometer score improvements. This progress was facilitated by our collaboration with Arm, who contributed valuable insights and improvements, including to identify and address inefficiencies in Chrome's PGO setup and inlining.
Chrome continuously improves the performance of its JavaScript and web rendering engines, V8 and Blink. Most optimizations are small in individual impact, but stacked together, these improvements add up and contributed most of the remaining Speedometer impact! Notable ones include:
To achieve the best possible performance, Android partners invest heavily in tuning the operating system's thread scheduling and frequency scaling policies, as well as improving the performance of the Silicon itself.
We worked closely with our partners to improve their tuning for Chrome and Speedometer. In particular, our collaboration with Qualcomm was very fruitful: By combining optimized scheduling policies with improved hardware performance, their newest Snapdragon 8 Elite mobile platform realized a 60-80% improvement in Speedometer 3.0 compared to its predecessor, resulting in class-leading web performance. This collaboration also highlighted important bottlenecks in Chrome's code, such as the need for improved PGO and opportunities in V8.
Speedometer 3.0 on Snapdragon 8 Gen 3 (left) compared to Snapdragon 8 Elite (right), Chrome M131
Faster Speedometer scores translate to improvements in real user interactions with web content, such as faster page loads and interactions. Back at M112, loading a Google Docs document on Pixel Tablet took more than 50% longer than it does today -- that's the effect of a doubled Speedometer score!
Chrome M112 vs. M129 on Pixel Tablet, loading a Google Doc (frame count)
[1] Speedometer 3 was released during M122, so results from Speedometer 2.1 are provided for a full picture. Measurements shown in graphs were taken on Pixel Tablet.
Last October, we introduced a new identity model on iOS (Chrome 118) and are excited to bring it to Android devices and Desktop soon. This model aligns closely with how you already use other Google apps and services.
When we first launched Chrome sync back in 2009, powered by the Google Account, our goal then, as it is today, was simple: help users access their bookmarks, passwords, tabs and more, across devices. At the time, this was best achieved by a sync model: synchronizing device data with your account and therefore requiring both sign-in and enabling sync.
Over the years, the digital world has changed and user expectations have evolved significantly. Cloud services emerged in 2010, and over the past 15 years, the concept of having a digital identity became more prevalent, especially through smartphones and mobile apps. Today, users increasingly expect to just sign in to get access to their stuff and sign out to keep it safe.
Given this evolution of technology and user norms, we’re continuing to make progress on transforming our legacy sync model into one that more seamlessly meets the expectation users have today. From the point of signing in to Chrome you’ll get access to your saved passwords, addresses, and other data from your Google Account. Where relevant, we’ll offer you the choice to sign into Chrome for a customized browsing experience on any device. For example, you can sign in and start to plan a trip on your phone during your commute, and then seamlessly finish it up on any device. Send tabs between your devices, find your bookmarks and use autogenerated passwords with ease.
As always, you have control - we strive to provide an excellent browser experience regardless of whether you choose to sign in or not. Additionally, saving your history and open tabs to your account remains a separate opt-in after signing into Chrome.
Stay tuned for updates on this change - already on iOS and coming to Android and Desktop soon.
ChromeOS will soon be developed on large portions of the Android stack to bring Google AI, innovations, and features faster to users.
Over the last 13 years, we’ve evolved ChromeOS to deliver a secure, fast, and feature-rich Chromebook experience for millions of students and teachers, families, gamers, and businesses all over the world. With our recent announcements around new features powered by Google AI and Gemini, Chromebooks now give us the opportunity to put powerful tools in the hands of more people to help with everyday tasks.
To continue rolling out new Google AI features to users at a faster and even larger scale, we’ll be embracing portions of the Android stack, like the Android Linux kernel and Android frameworks, as part of the foundation of ChromeOS. We already have a strong history of collaboration, with Android apps available on ChromeOS and the start of unifying our Bluetooth stacks as of ChromeOS 122.
Bringing the Android-based tech stack into ChromeOS will allow us to accelerate the pace of AI innovation at the core of ChromeOS, simplify engineering efforts, and help different devices like phones and accessories work better together with Chromebooks. At the same time, we will continue to deliver the unmatched security, consistent look and feel, and extensive management capabilities that ChromeOS users, enterprises, and schools love.
These improvements in the tech stack are starting now but won’t be ready for consumers for quite some time. When they are, we’ll provide a seamless transition to the updated experience. In the meantime, we continue to be extremely excited about our continued progress on ChromeOS without any change to our regular software updates and new innovations.
Chromebooks will continue to deliver a great experience for our millions of customers, users, developers and partners worldwide. We’ve never been more excited about the future of ChromeOS.
Posted by Prajakta Gudadhe, Senior Director, Engineering, ChromeOS & Alexander Kuscher, Senior Director, Product Management, ChromeOS
Today’s The Fast and the Curious post explores how Chrome achieved the highest score on the new Speedometer 3.0, an upgraded browser benchmarking tool to optimize the performance of Web applications. Try out Chrome today!
Speedometer 3.0 is a recently published benchmark for measuring browser performance that was created as an industry collaboration between companies like Google, Apple, Mozilla, Intel, and Microsoft. This benchmark helped us identify areas in which we could optimize Chrome to deliver a faster browser experience to all our users.
Here’s a closer look at how we further optimized Chrome to achieve the highest score ever Speedometer 3, by carefully tracking its recent performance over time as the updated benchmark was being developed. Since the inception of Speedometer 3 in May 2022, we've driven a 72% increase in Chrome’s Speedometer score - translating into performance gains for our users:
By looking at the workloads in Speedometer and in which functions Chrome was spending the most time, we were able to make targeted optimizations to those functions that each drove an increase in Chrome’s score. For example, the SpaceSplitString function is used heavily to turn space-separated strings such as those in “class=’foo bar’ ” into a list representation. In this function we removed some unnecessary bound checks. When we detect that there are duplicated stylesheets, we dedupe them and reference a single stylesheet instance. We made an optimization to reduce the cost of drawing paths and arcs by tuning memory allocations. When creating form editors we detected some unnecessary processing that occurs when form elements are created. Within querySelector, we were able to detect what selector was commonly used and create a hot-path for that.
We previously shared how we optimized innerHTML using specialized fast paths for parsing, an implementation that also made its way into WebKit. Some workloads in Speedometer 3 use DOMParser so we extended the same optimization for another 1% gain.
We worked with the Harfbuzz maintainer to also optimize how Chrome renders AAT fonts such as those used by Apple Mac OS system fonts. Text starts as a processed stream of unicode characters that is then transformed into a glyph stream that is then run through a state machine defined in the AAT font. The optimization allows us to determine more quickly whether glyphs actually participate in the rules for the state machine, leading to speed-ups when processing text using AAT.
An important strategy for achieving high performance is tiering up code, which is picking the right code to further optimize within the engine. Intel contributed profile guided tiering to V8 that remembers tiering decisions from the past such that if a function was stably tiered up in the past, we eagerly tier it up on future runs.
Another area of changes that drove around 3% progression on Speedometer 3 was improvements around garbage collection. V8’s garbage collector has a long history of making use of renderer idle time to avoid interfering with actual application code. The recent changes follow this spirit by extending existing mechanisms to prefer garbage collection in idle time on otherwise very active renderers where possible. Specifically, DOM finalization code that is run on reclaiming objects is now also run in idle time. Previously, such operations would compete with regular application code over CPU resources. In addition, V8 now supports a much more compact layout for objects that wrap DOM elements, i.e., all objects that are exposed to JavaScript frameworks. The compact layout reduces memory pressure and results in less time spent on garbage collection.
Posted by Thomas Nattestad, Chrome Product Manager
On the Chrome team, we believe it’s not sufficient to be fast most of the time, we have to be fast all of the time. Today’s The Fast and the Curious post explores how we contributed to Core Web Vitals by surveying the field data of Chrome responding to user interactions across all websites, ultimately improving performance of the web.
As billions of people turn to the web to get things done every day, the browser becomes more responsible for hosting a multitude of apps at once, resource contention becomes a challenge. The multi-process Chrome browser contends for multiple resources: CPU and memory of course, but also its own queues of work between its internal services (in this article, the network service).
This is why we’ve been focused on identifying and fixing slow interactions from Chrome users’ field data, which is the authoritative source when it comes to real user experiences. We gather this field data by recording anonymized Perfetto traces on Chrome Canary, and report them using a privacy-preserving filter.
When looking at field data of slow interactions, one particular cause caught our attention: recurring synchronous calls to fetch the current site’s cookies from the network service.
Let’s dive into some history.
Cookies have been part of the web platform since the very beginning. They are commonly created like this:
document.cookie = "user=Alice;color=blue"
And later retrieved like this:
// Assuming a `getCookie` helper method: getCookie("user", document.cookie)
Its implementation was simple in single-process browsers, which kept the cookie jar in memory.
Over time, browsers became multi-process, and the process hosting the cookie jar became responsible for answering more and more queries. Because the Web Spec requires Javascript to fetch cookies synchronously, however, answering each document.cookie query is a blocking operation.
document.cookie
The operation itself is very fast, so this approach was generally fine, but under heavy load scenarios where multiple websites are requesting cookies (and other resources) from the network service, the queue of requests could get backed up.
We discovered through field traces of slow interactions that some websites were triggering inefficient scenarios with cookies being fetched multiple times in a row. We landed additional metrics to measure how often a GetCookieString() IPC was redundant (same value returned as last time) across all navigations. We were astonished to discover that 87% of cookie accesses were redundant and that, in some cases, this could happen hundreds of times per second.
GetCookieString()
The simple design of document.cookie was backfiring as JavaScript on the web was using it like a local value when it was really a remote lookup. Was this a classic computer science case of caching?! Not so fast!
The web spec allows collaborating domains to modify each other’s cookies. Hence, a simple cache per renderer process didn’t work, as it would have prevented writes from propagating between such sites (causing stale cookies and, for example, unsynchronized carts in ecommerce applications).
We solved this with a new paradigm which we called Shared Memory Versioning. The idea is that each value of document.cookie is now paired with a monotonically increasing version. Each renderer caches its last read of document.cookie alongside that version. The network service hosts the version of each document.cookie in shared memory. Renderers can thus tell whether they have the latest version without having to send an inter-process query to the network service.
This reduced cookie-related inter-process messages by 80% and made document.cookie accesses 60% faster 🥳.
Improving an algorithm is nice, but what we ultimately care about is whether that improvement results in improving slow interactions for users. In other words, we need to test the hypothesis that stalled cookie queries were a significant cause of slow interactions.
To achieve this, we used Chrome’s A/B testing framework to study the effect and determined that it, combined with other improvements to reduce resource contention, improved the slowest interactions by approximately 5% on all platforms. This further resulted in more websites passing Core Web Vitals 🥳. All of this adds up to a more seamless web for users.
Timeline of the weighted average of the slowest interactions across the web on Chrome as this was released to 1% (Nov), 50% (Dec), and then all users (Feb).
By Gabriel Charette, Olivier Li Shing Tat-Dupuis, Carlos Caballero Grolimund, and François Doray, from the Chrome engineering team
