jina-embeddings-v5-text-nano Locally via LM Studio No-Internet Version

For an instant local deployment, running a pre-configured shell script is ideal.

Refer to the action plan below to initialize the model.

Hands-free setup: the system self-downloads the heavy model files.

The installer diagnoses your environment to deploy the most compatible profile.

📊 File Hash: dd10e2f6099099f441c0952bb35ba3bb — Last update: 2026-06-23



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: free: 80 GB on system drive for scratch space
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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