jina-embeddings-v5-text-nano Windows 11

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jina-embeddings-v5-text-nano Windows 11

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

Refer to the instructions below to proceed.

The loader auto-caches the model archive (several GBs included).

To save you time, the system will automatically determine efficient resource allocation.

đź–ą HASH-SUM: 2137f2b4ff4a1f4e2c32c71bb5f00ae9 | đź“… Updated on: 2026-06-30



  • Processor: next-gen chip for heavy context processing
  • RAM: enough space for background apps and OS overhead
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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