Magika vs Opsmeter — Find what caused your AI bill.
Overview
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Detailed Comparison
It leverages the power of cutting-edge deep learning to enhance the world of file type detection. It provides increased accuracy and support for a comprehensive range of content types, outperforming traditional tools with 99%+ average precision and recall. | Find what caused your AI bill. Opsmeter gives endpoint, user, model, and prompt-level AI cost attribution in one view. |
Available as a Python command line, a Python API, and an experimental TFJS version;
Trained on a dataset of over 25M files across more than 100 content types;
Achieves 99%+ average precision and recall, outperforming existing approaches;
After the model is loaded (this is a one-off overhead), the inference time is about 5ms per file | ndpoint/user/model/prompt-level AI cost attribution, Provider-agnostic telemetry ingest API, Token and latency tracking, Budget alerts (Pro+ plans), Plan-based ingest rate limits with Retry-After headers, Workspace-level dashboards and filters, Retention controls (raw + summary data) |
Statistics | |
GitHub Stars 8.9K | GitHub Stars - |
GitHub Forks 454 | GitHub Forks - |
Stacks 0 | Stacks 10 |
Followers 2 | Followers 1 |
Votes 0 | Votes 1 |
Pros & Cons | |
No community feedback yet | Pros
Cons
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Integrations | |
| No integrations available | |
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