A jailbroken PS5 can run AI models locally and offline after llama.cpp was ported to run natively, with greater access to the GPU and RAM.
The result is a clear improvement in speed. The Gemma 4 E4B model reaches 61 tokens per second, while Llama 3.2 3B reaches up to 124 tokens per second. The Qwen3.8-27B model achieves 20 tokens per second.
Native execution also allows up to 11.4 GiB of RAM to be used, compared with around 6.25 GiB when running through the CPU.creative assistant
From a PS5 That Can Run AI to a Machine Using the GPU for Processing
PS5LM is a port of llama.cpp that allows the PS5 to run language models locally and offline. Originally, the project operated as a payload on the CPU, injecting AI processing alongside the home screen and system services.
The latest fork changes the approach to native execution on the PS5, using the GPU through PS5_Vulkan. This removes the need to rely primarily on the CPU. The change allows the PS5 to allocate its resources to language models more effectively and opens the way to running larger models.
The Turning Point in the Latest PS5LM Fork
cobanov’s version runs as a payload on the CPU, so it can use only around 6 GiB, or approximately 6.25 GiB, of RAM. Using more memory could cause the home screen to freeze.
The fork by u/AdIllustrious7246 uses PS5_Vulkan, a RADV port for sending commands to the PS5’s GPU. This means the workload no longer has to be handled solely by the CPU and allows up to 11.4 GiB of RAM to be used. The change improves both model size and processing speed.
When the PS5 Stops Playing Games and Becomes an AI Assistant
When the PS5 is not being used for gaming, it can run language models offline and act as an AI assistant without sending data to a server for processing. This is happening on a game console that was not originally designed to be an AI workstation.
With the GPU assisting processing, models such as Llama 3.2 3B reach 124 tokens per second, while Gemma 4 E4B reaches 61 tokens per second, making conversations reasonably smooth. The llama.cpp web UI also allows other devices on the local network to chat with the model through a browser.
Where It Fits in the PS5 Homebrew World
This project is homebrew work built on PS5_Vulkan, a port of the RADV graphics driver for sending commands to the PS5’s GPU. Since the GPU was originally locked down, this opens the way for projects such as running LLMs on the console.
This is not an official Sony feature and still requires a jailbroken PS5. llama.cpp runs as a native app on the unlocked system, providing greater access to the GPU and RAM than the CPU-based payload approach.
The Previous Version Compared with the Native-Running Fork
The previous version ran as a payload on the CPU and therefore had to share RAM with the home screen and system services, limiting usage to approximately 6–6.25 GiB. Loading a large model could cause the system to freeze or crash.
The latest fork runs llama.cpp natively and uses the GPU through PS5_Vulkan, allowing up to 11.4 GiB of RAM to be used and supporting larger models. The results include Qwen3.8-27B at 20 tokens per second, along with a dashboard showing tokens per second, GPU/CPU usage, temperature, and power consumption in real time.
Real-World Speed Figures
Test results report that Qwen3.8-27B reaches 20 tokens per second, Gemma 4 E4B reaches 61 tokens per second, and Llama 3.2 3B reaches 124 tokens per second.
The figures vary according to model size. Larger models such as Qwen3.8-27B require more processing time, while smaller models such as Llama 3.2 3B generate responses significantly faster.
What Kind of Use Shows the Difference?
The dashboard provides a live view of token-generation speed and immediately shows GPU, CPU, power, temperature, and memory allocation between the model and KV cache. This is useful for anyone who wants to see how hard the console is working when running a large model.
The llama.cpp web UI allows users to chat with the model through a browser on another device on the local network, such as a computer or nearby device, while the PS5 handles processing in the background.
Options Available in the Source
Running llama.cpp as a CPU payload is quick to set up, but it can use only around 6 GiB, or approximately 6.25 GiB, of memory. Using more could cause the home screen to freeze. The native fork running through PS5_Vulkan provides greater access to the GPU and RAM, allowing larger models to run.
Another option is to use the PS5 normally for gaming, which remains the console’s primary purpose and requires no system modifications. The source does not provide information about competing products or other systems for direct performance comparisons.
Key Advantages and Limitations
Advantages: A jailbroken PS5 can run language models locally and offline, using the GPU to accelerate token generation. It supports 27B models and can use up to 11.4 GiB of RAM. The dashboard displays token-generation speed, GPU/CPU usage, temperature, and power consumption, while the llama.cpp web UI allows connections from other devices.
Limitations: A jailbroken PS5 is required because GPU access was originally locked down. Speed and model size still depend on the console’s hardware. The CPU-based version has limited RAM and may cause the system to freeze, while the source does not specify the cost of installation or modification.
The Trade-Offs of Making the PS5 Run AI
The main cost is owning a jailbroken PS5 and accepting that the console’s GPU is neither the fastest nor equipped with the most RAM for AI workloads. Models therefore still need to be chosen according to the available resources.
Memory must be shared between the model and the KV cache, limiting usable capacity. The dashboard helps track GPU, CPU, power draw, and temperature, providing visibility into the console’s workload while running AI locally.
What This Project Says About Gaming Hardware
PS5_Vulkan provides access to the PS5’s GPU, allowing the console to run local AI models in addition to playing games. This demonstrates that gaming hardware can still have potential for other homebrew applications when hardware-access restrictions are removed.
However, this work is not evidence that the PS5 is suitable for large-scale AI workloads, since the source states that the console’s GPU is not the fastest and that it does not have the most RAM among hardware designed for this type of work.
From Game Console to Home AI Experiment
The PS5LM fork can turn an idle PS5 into a home AI experimentation machine by running models through the GPU and using up to 11.4 GiB of RAM. It also provides a dashboard with live token-generation speed, GPU/CPU usage, temperature, and power draw, while allowing users to chat with the model through a browser on a device connected to the same network.
This project demonstrates the potential of homebrew and repurposing existing hardware, even though the PS5 does not have the fastest GPU or the most RAM. It will be interesting to see what other forms of homebrew development emerge as access to the GPU becomes possible.