How to Install jina-embeddings-v5-text-nano Locally (No Cloud)

The most efficient approach for a local installation is leveraging Docker containers.

Just follow the guidelines provided below.

The installer auto-downloads and deploys the entire model pack.

The setup file includes a feature that instantly optimizes all configurations.

🔐 Hash sum: 1654e022c7d785eb029ae5f7eff6efcc | 📅 Last update: 2026-06-29
  • CPU: AVX2/AVX-512 instruction set required for llama.cpp
  • RAM: enough space for background apps and OS overhead
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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:

Parameters 2 million
Size (MB) 7.8
Latency (ms) <5
Throughput (tokens/s) 2000
Supported Languages 30
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