embeddings onnx manticore developer-tools

14× faster embeddings: how we rebuilt the ONNX path in Manticore

manticoresearch.com

July 3, 2026

14 min read

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Summary

Manticore has rebuilt the ONNX path for Auto Embeddings, achieving a 14× increase in speed for converting text columns into vectors. The previous method using SentenceTransformers and Candle limited throughput, resulting in low document processing rates and serialized concurrent calls.

Key Takeaways

The new ONNX Runtime backend in Manticore Search 27.1.5 is approximately 14× faster than the previous SentenceTransformers/Candle path for embedding models.
The ONNX path achieves document processing speeds ranging from 70 to 230 docs/sec, compared to the previous range of 5 to 11 docs/sec.
Single-insert latency with the new backend is around 14 ms for a single client and 56 ms under 8-way concurrent load, significantly lower than the 200+ ms latency of the old path.
The new backend allows for improved performance tuning options, enabling users to achieve higher throughput by adjusting batch sizes and concurrency.

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