---
license: mit
---

# TurboPrefill
![TurboPrefill RTX 5060 Ti](Turboprefill_8xRTX5060ti.png)

[GitHub Repository](https://github.com/sergey-automation/TurboPrefill)

Multi-GPU prefill acceleration for llama.cpp.

TurboPrefill is an experimental scheduling modification for llama.cpp designed to improve long-context prefill throughput in multi-GPU layer-split configurations.

## Key Results

* Up to **2.23× faster prefill**
* Tested with **GPT-OSS-120B**
* No changes to model outputs
* Decode path remains unchanged

## Tested Multi-GPU Platforms

TurboPrefill is based on general multi-GPU scheduling principles and has been tested across multiple NVIDIA GPU generations and cluster sizes.

* 8× NVIDIA RTX 5060 Ti 16GB (Blackwell architecture, 2025)
* 4× NVIDIA RTX 3090 (Ampere architecture, 2020)
* 10× NVIDIA P104-100 (Pascal architecture, 2016)
* 
TurboPrefill has been successfully tested across three NVIDIA GPU generations spanning nearly a decade of hardware development.

## Additional Validation

![TurboPrefill Pascal](Turboprefill_Pascal.png)

Results were also reproduced on Pascal-generation hardware using multi-GPU P104-100 systems.

## Project Status

Public release v1.0.0.

TurboPrefill is an experimental open-source optimization for llama.cpp focused on accelerating long-context multi-GPU prefill workloads.

## GitHub Repository

https://github.com/sergey-automation/TurboPrefill

Industrial Systems Architect: Serhii Trykhlieb