Deploy jina-embeddings-v5-text-nano No Python Required

Deploying this model locally is quickest when done via Docker.

Use the instructions provided below to complete the setup.

The smart installation system will instantly find the perfect configuration for your specific hardware.

📤 Release Hash: 234c8dc4190a8e77c4bff37b629c5514 • 📅 Date: 2026-06-26 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: 100 GB for multi-modal model vision components Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The jina-embeddings-v5-text-nano model delivers compact yet high‑quality text embeddings optimized for edge devices. With only 2 million parameters, it achieves competitive performance on semantic similarity tasks while maintaining a small memory footprint. Its inference latency is under 5 ms on typical CPUs, making it ideal for real‑time applications that require fast processing. The model supports multiple languages and preserves contextual nuances better than earlier nano‑sized alternatives. Key metrics are summarized in the following table:

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