Enable large AI models to run efficiently on commodity hardware
GGML is a tensor library that lets you run advanced machine learning models on everyday devices without needing expensive servers. It supports high-performance inference with features like integer quantization, making AI more accessible and cost-effective. This is perfect for developers and hobbyists who want to experiment with AI on their own hardware.
Works on various hardware with no third-party dependencies
Supports integer quantization for improved efficiency
Keeps the codebase small and simple for easy use
Freely available under MIT license for community contributions
Zero memory allocations during runtime for optimal speed
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Recent data shows that GGML has 140.1K monthly visits (79.5% increase from the previous month), 45.0% bounce rate, and average 4.69 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by United States contributing 16% of total traffic. SEO performance is shown by 5 tracked keywords, with "ggml" being the top-performing keyword with 2.7K monthly searches. See below for more info.
Monthly Visits
140.1K
Pages per Visit
4.69
Bounce Rate
45.0%
Average Time on Site
1m 46s
| SEO Keyword | Volume | CPC |
|---|---|---|
| ggml | 2.7K | - |
| whisper.cpp | 21.7K | - |
| whisper german model | 190 | - |
| extrackt text from audio | 100 | - |
| whisper.wasm | 80 | - |
| Source | Traffic Share |
|---|---|
| Direct | 31% |
| Search | 25% |
| Social | 4% |
| Referrals | 39% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 16% |
 | 8% |
 | 6% |
 | 5% |
 | 5% |
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