Doom Runs on a Custom CPU Designed by GPT 5.6 Sol in a Turing Complete Sandbox

The breakthrough: Doom on a purpose built processor

In a recent demonstration that captured the attention of hardware hobbyists, a custom central processing unit (CPU) engineered with the assistance of GPT 5.6 Sol successfully executed the classic first‑person shooter Doom. The visual experience was presented as a game viewport layered over a dynamic schematic of the processor, all within the interactive sandbox provided by Turing Complete.

Designing the processor with GPT 5.6 Sol

The creator, an avid member of the open‑source hardware community, leveraged the generative capabilities of GPT 5.6 Sol to outline the instruction set, pipeline stages, and memory hierarchy. The resulting design was synthesized onto a field‑programmable gate array (FPGA) using a standard hardware description language. By iterating on the model in real time, the developer refined timing constraints and eliminated bottlenecks that would have prevented a real‑time game from running.

Architecture highlights

Eight‑stage pipeline with branch prediction
32‑bit RISC instruction set optimized for raster graphics
Integrated texture cache of 256 KB
Hardware‑accelerated fixed‑point math unit
Clock speed of 200 MHz, sufficient for the original Doom engine

The sandbox environment

Turing Complete offers a web‑based platform where users can assemble virtual hardware components, connect them with simulated wiring, and observe real‑time behavior. In this case, the custom CPU was placed alongside a virtual display controller, audio output module, and input handler. The sandbox visualizes signal flow, allowing the audience to see how each instruction propagates through the pipeline while the game runs.

How the demo works

Loading the game

The original Doom binary was compiled for the custom instruction set using a cross‑compiler generated from the same GPT 5.6 Sol model. After loading the binary into the CPU’s instruction memory, the sandbox emulated the boot process, initializing graphics mode and reading level data from a virtual disk image.

Visual overlay

As the player navigates the map, the viewport appears in the center of the screen. Behind it, a semi‑transparent schematic of the CPU pulses in sync with clock cycles. Each time the processor fetches an instruction, the corresponding block in the schematic highlights, giving viewers a clear picture of the hardware‑software interaction.

Significance for hardware innovation

Demonstrating Turing completeness

Running a full game like Doom proves that the processor can perform any computation that a general‑purpose computer can, satisfying the criteria for Turing completeness. This achievement is more than a novelty; it validates the design methodology used by the developer and showcases the power of modern design tools.

Potential applications

Beyond gaming, a custom CPU with a dedicated graphics pipeline could be repurposed for embedded vision systems, low‑power simulators, or educational platforms that teach computer architecture. The ability to overlay execution traces in real time also opens new possibilities for debugging complex firmware.

Community reaction and next steps

The demonstration quickly spread across forums dedicated to FPGA development, retro gaming, and computer engineering. Participants praised the clarity of the visual overlay and the transparency of the design files, which were released under an open‑source license.

Future work outlined by the creator includes:

Porting additional classic titles such as Wolfenstein 3D and Quake.
Increasing clock speed to 400 MHz for smoother frame rates.
Integrating a hardware audio synthesizer to replace the software mixer.
Publishing a step‑by‑step tutorial series on the Turing Complete platform.

For those interested in the technical details, the full hardware description files are available on the project’s repository, and a live walkthrough can be viewed on the developer’s streaming channel.

As the line between software‑generated design and physical hardware continues to blur, projects like this illustrate how collaborative tools can accelerate innovation, turning ambitious concepts into tangible, working machines.