> For the complete documentation index, see [llms.txt](https://docs.load.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.load.network/using-load-network/compute.md). # Compute Combining the Load EVM with custom HyperBEAM devices enables a wide range of options, from **smart contracts** to **WASM workers** to **serverless GPU functions**. In this page we will briefly go over the different options within the extended Load Network ecosystem. #### Native EVM compute The Load EVM offers native EVM compute with typical smart contracts, blobs and calldata standards that are all 1:1 compatible with Ethereum and other EVM networks. As a specialized storage and DA chain, the Load L1 is optimized for [high throughput](/about-load-network/key-features.md) to enable data-intensive dApps. [Connect to Load Alphanet RPC here](/using-load-network/network-configurations.md). #### Lua / WASM compute Load Network is a hybrid of the EVM and AO's HyperBEAM. The Load Network team runs HyperBEAM instances (permissionless nodes running the AO compute canonical stack), therefore it's possible to leverage the highly scalable AO compute (processes, hyper-aos, Lua serverless functions) within the Load stack. [Connect to a node here](/load-network.md). Additionally, we have developed an EVM compute layer (bytecode calculator) as a HyperBEAM device. [Learn more](/load-hyperbeam/evm-1.0-device.md). #### GPU compute More over in HyperBEAM land, the Kernel Execution Machine ([\~kem@1.0 device](/load-hyperbeam/kem-1.0-device.md)) allows for quasi-arbitrary GPU-instructions compute execution for `.wgsl` functions (shaders, kernels). [Get started](/load-hyperbeam/kem-1.0-device.md). #### Reth Execution Extensions (ExEx) Although this is not compute for the user/consumer level, Load maintains several Reth execution extensions (post block-execution compute logic) that can benefits the Reth and the wider EVM developers set. [Learn more](/load-network-exex/about-exexes.md). --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.load.network/using-load-network/compute.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.