Deploy jina-embeddings-v5-text-nano Easy Build

The fastest method for installing this model locally is by using Docker.

Simply follow the directions outlined below.

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1-click setup: the app automatically fetches the large weight files.

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

🔐 Hash sum: abd60ca9f49fe2a2ebd09b733ef03666 | 📅 Last update: 2026-06-27



  • Processor: next-gen chip for heavy context processing
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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