Teardown Reveals NVIDIA GPUs Secretly Host Up to 30 Internal RISC-V Cores Running Autonomous Firmware

The Three-Question Framework

What Happened?

Hardware reverse-engineers and open-source driver developers published an exhaustive firmware analysis of modern Nvidia GPUs, revealing that chips across the Ada Lovelace, Hopper, and Blackwell generations contain between 10 and 30 proprietary 64-bit RISC-V cores embedded directly on the die. These cores, which operate invisibly beneath the primary CUDA compute SMs, form a distributed microcontroller fabric known as the GPU System Processor (GSP).

Why It Matters

For decades, Nvidia graphics cards relied on proprietary Falcon microcontrollers and host CPU kernel drivers to manage hardware state. By silently transitioning its entire internal control fabric to customized RISC-V cores running an embedded real-time microkernel, Nvidia offloaded memory management, power telemetry, and thermal throttling entirely onto the GPU die, while creating a hardened firmware barrier that protects internal GPU silicon IP from external driver reverse-engineering.

What Could Happen Next

The open-source Linux kernel community (including the Nouveau and NVK Vulkan driver teams) is utilizing the documented GSP RISC-V firmware interfaces to achieve 100% feature parity with proprietary Nvidia drivers without relying on closed-source host kernel modules.

Executive Key Takeaways

Hidden RISC-V Supercluster: Modern Nvidia GPUs embed up to 30 custom 64-bit RISC-V cores directly on the die.

Falcon Architecture Retired: Completes Nvidia's long-term migration away from proprietary Falcon microcontrollers.

On-Die Driver Offloading: The GPU System Processor (GSP) executes driver state machines and scheduling autonomously on-chip.

Open-Source Driver Breakthrough: Provides documented firmware targets that allow open Linux drivers (Nouveau/NVK) to achieve full performance.

On September 20, 2026, a forensic teardown published by hardware security analysts and open-source driver contributors confirmed a long-suspected open secret of modern silicon design: every high-performance Nvidia GPU shipped today secretly houses a distributed cluster of up to thirty custom 64-bit RISC-V processor cores operating on the die alongside its primary graphics and tensor cores.

To the operating system and the end user, an Nvidia accelerator presents itself as a monolithic computing engine defined by thousands of CUDA cores and hundreds of Tensor Cores. However, as GPU architectures evolved into massive multi-chip modules dissipating up to 1,000 watts of power, managing the silicon's physical operating parameters became too complex for the host CPU to oversee over an external PCIe link.

Historically, Nvidia utilized proprietary on-die microcontrollers based on its in-house 'Falcon' (Fast Logic Controller) architecture to handle video decoding, thermal pacing, and memory initialization. But Falcon's 32-bit address space and limited instruction set became an insurmountable bottleneck as GPUs scaled past 100 billion transistors. Beginning quietly with the Ada Lovelace generation and expanding dramatically in Hopper and Blackwell, Nvidia engineered a wholesale replacement, adopting custom 64-bit RISC-V cores across its silicon lineup.

The reverse-engineering teardown reveals that modern Blackwell B200 and Hopper H100 GPUs deploy an entire internal hierarchy of RISC-V cores. At the apex sits the primary GPU System Processor (GSP), a multi-core RISC-V CPU running an encrypted, real-time microkernel that handles memory allocation, command queue scheduling, and PCIe power state transitions.

Subordinate RISC-V microcontrollers are distributed across memory crossbars and voltage domains, continuously executing autonomous control loops to balance current draw across phases, throttle individual compute clusters experiencing thermal hot-spots, and supervise cryptographic attestation for confidential computing workloads.

For the open-source software ecosystem, the disclosure represents a major triumph. In the past, writing open-source Linux drivers for Nvidia GPUs was an agonizing battle against undocumented hardware registers. Because modern Nvidia drivers delegate low-level hardware control to the GSP RISC-V firmware, open-source projects like Nouveau and the Mesa NVK driver can achieve full clock speeds and power management simply by passing standardized command buffers to the on-die RISC-V processor.

The findings highlight the quiet, unstoppable triumph of the open RISC-V instruction set architecture: even the world's most dominant proprietary silicon vendor has adopted RISC-V as the indispensable nervous system of its flagship artificial intelligence hardware.

The Three-Question Framework

What Happened?

Why It Matters

What Could Happen Next

Executive Key Takeaways

Primary Sources & Citations