N64 Emulation Revolution: Rollback Netcode Added to Entire Library
The RMG-K emulator has received a major update, bringing rollback netcode to the entire Nintendo 64 library and fundamentally changing online retro gaming.

Key Points
- Rollback netcode implemented for the entire Nintendo 64 library via RMG-K emulator.
- Massive reduction in input delay, enabling cross-continental play with only 4 frames of lag.
- Utilization of the GekkoNet framework to simplify the implementation process.
- Controversy sparked over the use of AI tools in the development of the fork.
- Feature currently supports two-player sessions only.
I have always felt that the original Super Smash Bros. offers a level of raw, combo-heavy satisfaction that modern titles struggle to replicate. Yet, in 2026, finding a reliable way to play these classics with other humans is an exercise in frustration. Most emulators provide netplay, but the reliance on traditional delay-based systems means that any game requiring twitch reactions—like the frantic pace of Smash or the precision needed in GoldenEye—feels like you're playing through a swamp. That is, until this week's breakthrough. On May 14, 2026, the RMG-K emulator, a fork of the well-known RMG Nintendo 64 emulator, received an update that brought rollback netcode to its entire library. While this is currently limited to two-player sessions, the implications are massive. If you aren't familiar with the tech, rollback netcode is the holy grail of online multiplayer. It’s the reason why fighting game communities lose their collective minds when a developer announces it. It essentially makes fast-paced games feel responsive, even when your internet connection is far from ideal. In a standard delay-based system, the game waits for your input to travel across the internet and reach the other player's machine before it registers your move on screen. If your ping is high, the game stutters. Rollback, conversely, makes a prediction about what your input will be. If it predicts correctly, the game moves on instantly. If it’s wrong, it quickly corrects the state. It’s a magic trick of software engineering, and it makes the difference between a game that is unplayable and one that feels like local couch co-op. I was genuinely struck by a video shared by Bluesky user Grasluu00, who demonstrated GoldenEye multiplayer using this new feature. The results were staggering: they managed to play from Spain all the way to Australia with just 4 frames of delay. Before this implementation, they were forced to endure 9 frames of lag. That isn’t just a minor improvement; that is the difference between a competitive experience and a slideshow. The responsiveness is, frankly, transformative. This implementation relies on the GekkoNet framework, which was highlighted by creator Heat on X. Interestingly, this same framework is being utilized for a fan project to bring the PlayStation 2 version of Street Fighter 3: 3rd Strike to PC. Programmer NyxTheShield, who worked on the RMG-K rollback implementation, made a comment that caught my eye: he claimed that GekkoNet did the heavy lifting and that adding rollback was "honestly not that hard." It’s fascinating to see how far we’ve come; what once seemed like wizardry is now becoming a standardized, accessible practice for open-source developers. However, the project hasn't been without its controversy. The original creator of the RMG emulator, Rosalie241, expressed significant frustration on Reddit. They criticized the RMG-K fork for its reliance on AI-assisted coding, labeling the practice as "vibe coding" and expressing sadness that others had taken their years of hard work and "vibe coded" changes using tools like Claude. Whether you agree with the ethical concerns or not, it highlights a growing rift in the software community: the tension between traditional, manual development and the speed afforded by modern AI assistants. For their part, the developers behind RMG-K, including NyxTheShield and CigNus, have been transparent about their use of AI. They’ve described tools like Codex as an "automation/helper" that is now standard in workspaces across the globe. From where I stand, while the frustration of the original creator is understandable, the reality is that this technology is now an inescapable part of the development landscape. If it results in better, more accessible software for the end user, the debate becomes much more complex. Ultimately, what matters here is the accessibility of our gaming history. We are seeing a shift where 30-year-old hardware limitations are being bypassed by modern software solutions. This isn't just about playing Smash 64 online; it’s about ensuring these games remain part of our modern cultural discourse. Will we see other emulators follow suit? I certainly hope so. The question now isn't if rollback can be implemented, but how quickly we can get it into the hands of every retro gamer out there.
The Rollback Revolution
The introduction of rollback netcode to the RMG-K emulator is a game-changer for retro gaming. By predicting inputs rather than waiting for them, this technology effectively eliminates the sluggish feel that has plagued N64 online play for years. Testing has shown that games like GoldenEye and Super Smash Bros. are now viable for competitive play across vast distances. Thanks to the GekkoNet framework, the technical barrier to implementing this feature has been significantly lowered, promising a brighter future for online retro gaming.
Coding Ethics and AI
The update has sparked a heated debate regarding the use of AI in software development. The original creator of the RMG project expressed disappointment over the use of AI to 'vibe code' changes into their existing codebase, sparking a conversation about the value of human-led development. Despite the controversy, the developers of RMG-K maintain that AI is simply a modern tool for automation. This tension between traditional coding practices and AI-assisted workflows is likely to continue, but for the average user, the focus remains on the improved functionality provided by the update.
This article was drafted with AI assistance and editorially reviewed before publication. Sources are listed below.