Ggml.ai

What is Ggml.ai?

GGML.ai is a C-based tensor library for machine learning that makes it possible to run large AI models on regular hardware, without specialized equipment. It supports 16-bit float and integer quantization for more efficient model execution, along with automatic differentiation and optimization tools like ADAM and L-BFGS.

The library is optimized for Apple Silicon and x86 architectures. For web applications, it supports WebAssembly and WASM SIMD, with zero runtime memory allocations and no external dependencies, making on-device inference efficient.

GGML.ai powers well-known projects such as whisper.cpp for speech-to-text and llama.cpp for large language model inference. The team encourages contributions through an open-core development model under the MIT license and is looking for full-time developers passionate about on-device AI.

Who created Ggml.ai?

Georgi Gerganov is the founder of ggml.ai, leading development of on-device inference technology. The company has received early support from investors Nat Friedman and Daniel Gross. Its focus is building a C-based tensor library designed to handle large models and perform well across a variety of hardware, with particular emphasis on Apple Silicon optimization. The project values community input and operates with an open-core development model under the MIT license.

What is Ggml.ai used for?

• Speech-to-Text: whisper.cpp provides speech-to-text solutions built on GGML.
• Large Language Models: llama.cpp uses GGML for efficient inference of Meta’s LLaMA models.
• Apple Silicon Optimization: Tuned specifically for Apple Silicon hardware, offering efficient processing and lower latency on Apple devices.
• Web Applications: WebAssembly and WASM SIMD support bring machine learning to the browser.
• Commodity Hardware: Enables large models and high-performance computation on standard, everyday hardware.
• Broad Architecture Support: Optimized for both Apple Silicon and x86.
• Clean Codebase: No third-party dependencies, keeping the code minimal and manageable.
• Guided Language Output: Supports guided generation to improve human-computer interaction.
• Open Development: Open-core model under the MIT license, welcoming community contributions.

GGML.ai’s approach is to advance AI at the edge with a simple, open library that the community can explore and build on.