Running SigLIP 2 on CPU with Rust+ONNX
kuaythrone · reddit · 2026-07-18
The author is building a robotics data platform handling images, videos, and text metadata simultaneously.
Their approach splits the multimodal embedding process of SigLIP 2 into two pipelines:
- The GPU handles batch, asynchronous image/video embedding and index building.
- A lightweight Rust + ONNX Runtime service processes real-time text queries on the CPU.
Since text and images ultimately share the same embedding space, text can directly search the image index built by the GPU. The author finds this split highly practical: reserving scarce GPUs for high-throughput multimodal ingestion while scaling the query side with standard CPU machines. They are also curious if others are using Rust for similar low-latency inference services.
More from Infra
- China’s AI arms race is increasingly defined by chips, data centers, and open models — BenBajarin · 2026-07-22
- Agent search bottlenecks are now about variance, not raw latency — rohanpaul_ai · 2026-07-22
- Gavin Baker argues Nvidia may be one of open source AI’s biggest supporters — GavinSBaker · 2026-07-22
- AI Power Demand Exposes US Energy Gap, Urging Shift from Scarcity to Abundance — bradneuberg · 2026-07-22
- Gavin Baker says Nvidia’s $630B figure would be system revenue, not all Nvidia’s — GavinSBaker · 2026-07-22
- A Firecracker-based platform says it can host 6,000 AI agents on one 256 GB server — maritime_sh · 2026-07-22