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Fast self-hosted embedding engine for search, RAG, and reindexing workloads on NVIDIA GPUs. Built in Rust + TensorRT for teams that care about scale, cost, and control.

0 starsRust

I embedded 685M public texts in 32 minutes (on 8x A100, Rust, TensorRT)

by ddayanov·Jun 4, 2026·3 points·1 comment

AI Analysis

●●SolidWizardryBig Brain

3.6x faster than Hugging Face TEI on same hardware with zero Python overhead at runtime.

Strengths
  • Production-verified numbers: 685M texts embedded with cost breakdown at $0.01 per 1M messages.
  • Native TensorRT in Rust eliminates Python GIL and runtime serialization bottlenecks.
  • 60 models supported out of the box with automatic ONNX export and TensorRT compilation.
Weaknesses
  • NVIDIA-only — no AMD, Intel, or Apple Silicon support despite growing alternative GPU markets.
  • Embedding infrastructure is crowded with TEI, Fastembed, and SentenceTransformers already established.
Target Audience

ML engineers running large-scale embedding pipelines on NVIDIA GPUs

Similar To

Hugging Face TEI · Fastembed · SentenceTransformers

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