Model reference · open weights
jina-embeddings-text-nano is an open-weight embedding model from jinaai, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
jina-embeddings-v5-text-nano jina-embeddings-v5-text-nano is the fifth generation of Jina AI's multilingual embedding models, released on February 18, 2026. For higher performance at a larger size, see jina-embeddings-v5-text-small. Elastic Inference Service | ArXiv | Release Note | Blog Model Overview jina-embeddings-v5-text-nano scores 71.0 average on MTEB English v2 and 65.5 on MMTEB with only 239M parameters, matching or exceeding all other sub-500M embedding models including KaLM-mini-v2.5 (494M) and Gemma-300M (308M). Built on EuroBERT-210M and trained by combining embedding distillation from Qwen3-Embedding-4B with task-specific contrastive losses, it supports multilingual text up to 32K tokens and produces embeddings robust under truncation and binary quantization. Training and Evaluation For training details and evaluation results, see our technical report. Usage The following Python packages are required: - transformers=4.57.0 - torch=2.8.0 - peft=0.15.2 Optional / Recommended - flash-attention: Installing flash-attention is recommended for improved inference speed and efficiency, but not mandatory. - sentence-transformers: If you want to use the model via the sentence-transformers interface, install this package as well. The fastest way to use v5-text in production. Elastic Inference Service (EIS) provides managed embedding inference with built-in scaling, so you can generate embeddings directly within your Elastic deployment. See the Elastic Inference Service documentation for setup details. We provide separate model versions for each task (retrieval, text-matching, classification, clustering). For each model, the task-specific adapter is merged into the base model weights. This modification enables simpler compatibility with vLLM. Instructions and usage examples for each task are available in their respective model repositories: - jina-embeddings-v5-text-nano-retrieval - jina-embeddings-v5-text-nano-text-matching - jina-embeddings-v5-text-nano-classification - jina-embeddings-v5-text-nano-clustering We provide separate model versions for each task (retrieval, text-matching, classification, clustering). For each model, the task-specific adapter is me
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | jinaai |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 212M |
| Context | 8k tokens |
| Variants | 1 |
| Runs with | transformers |
| Based on | EuroBERT/EuroBERT-210m |
| Released | 2026-01-22 |
| Popularity | 133k downloads / month |
| Likes | 98 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| jina-embeddings-v5-text-nano | 212M | BF16 | ~0.5 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys jina-embeddings-text-nano for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (jina-embeddings-text-nano below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"jina-embeddings-text-nano","input":"text to embed"}'
Licence
The weights are open but cc-by-nc-4.0 needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗
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