GGML
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About
GGML is a low-level, cross-platform tensor library for machine learning, designed to bring large AI models and high performance to commodity hardware. It features integer quantization support, broad hardware compatibility, and zero third-party dependencies, with no memory allocations during runtime. It powers projects like llama.cpp and whisper.cpp. The project emphasizes simplicity, open-source development under the MIT license, and encourages exploration. Founded by Georgi Gerganov with pre-seed funding from Nat Friedman and Daniel Gross, ggml.ai supports its ongoing development. They are hiring developers for on-device inference and can be contacted for business inquiries and enterprise deployment.
Platform
Features
• no third-party dependencies
• zero memory allocations during runtime
• broad hardware support
• integer quantization support
• low-level cross-platform implementation
• minimal codebase
• open core (mit license)
Pricing Plans
Free
Free Plan• Low-level cross-platform implementation
• Integer quantization support
• Broad hardware support
• No third-party dependencies
• Zero memory allocations during runtime
• Open-source under MIT license
Job Opportunities
There are currently no job postings for this AI tool.
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