Reducing Nvidia reserved VRAM from 380 MiB to 31 MiB via kernel module patching

Description and use

**Project Summary:** This open-source project reduces Nvidia reserved VRAM from 380 MiB to 31 MiB via kernel module patching, offering a potential solution for workflows that require optimized VRAM utilization.

**Value Proposition:** The project's value lies in its ability to free up significant amounts of VRAM, which can be beneficial for applications that require large amounts of memory, such as data science, machine learning, or video editing. By reducing the reserved VRAM, users can allocate more resources to their applications, potentially leading to improved performance and efficiency.

**Practical Adoption Path:** To adopt this project, users need to manually inspect the code and ensure it aligns with their specific workflow and system configuration. This involves verifying the license, maintenance, documentation, issues, and release cadence before integrating the patch into their kernel module. Due to the limited integration signals and quality signals, users should exercise caution and perform thorough checks before adopting this project in production environments.

**Production Readiness:** The project is considered medium-production ready, making it suitable for prototypes or internal workflows where dependency and maintenance checks can be performed before deployment. However, due to the limited quality signals and potential risks associated with kernel module patching, users should exercise caution and thoroughly evaluate the project's suitability for their production environments.

Use in a workflow

Reducing Nvidia reserved VRAM from 380 MiB to 31 MiB via kernel module patching may be useful when its README and activity match a concrete workflow.

Limitations and review notes

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.