---
last_updated: 2026-07-20
tags: [embedding, jina, cloud, local, farsi, insurance, rag, cheap]
source: import-knowledge
---

# Jina AI — jina-embeddings-v3

## Overview

Available as both cloud API and local model. Cheapest cloud option with explicit Farsi support. **⚠️ Local model has non-commercial license (CC-BY-NC-4.0).**

## Cloud API

- **Type**: Cloud
- **Provider**: Jina AI
- **Price**: ~$0.02 per 1M tokens ([source](https://jina.ai/pricing/))
- **Max input tokens**: 8,192
- **Embedding dimensions**: 1024 (Matryoshka — resizable)
- **Language coverage**: 89 languages including Farsi
- **Persian benchmark**: No public Persian-specific scores. Strong MTEB multilingual.

## Local Model

- **Parameters**: ~568M
- **VRAM (fp16)**: ~1.1 GB
- **License**: CC-BY-NC-4.0 ⚠️ (non-commercial!) — **verify for enterprise use**
- **Model card**: https://huggingface.co/jinaai/jina-embeddings-v3

## Pros

- Cheapest cloud option: ~$0.02/1M tokens
- 89 languages including Farsi
- Task-specific adapters (retrieval, clustering, classification)
- Matryoshka support (resizable dimensions)
- 8K context
- ColBERT/late interaction support

## Cons

- Local model is CC-BY-NC (non-commercial) — verify for enterprise
- Smaller company — less enterprise track record
- Pricing page not transparent (SPA, not standard display)

## API Test — Curl

**Endpoint**: `POST https://api.jina.ai/v1/embeddings`
**Auth**: `Authorization: Bearer $JINA_API_KEY`
**Get key**: https://jina.ai/api-keys

### For queries

```bash
curl -s https://api.jina.ai/v1/embeddings   -H "Content-Type: application/json"   -H "Authorization: Bearer $JINA_API_KEY"   -d '{
    "model": "jina-embeddings-v3",
    "input": ["بیمه نامه شخص ثالث چیست؟"],
    "task": "retrieval.query"
  }' | python3 -m json.tool
```

### For document chunks (indexing)

```bash
curl -s https://api.jina.ai/v1/embeddings   -H "Content-Type: application/json"   -H "Authorization: Bearer $JINA_API_KEY"   -d '{
    "model": "jina-embeddings-v3",
    "input": ["بیمه نامه شخص ثالث شامل پوشش خسارات مالی و جانی است."],
    "task": "retrieval.passage"
  }' | python3 -m json.tool
```

### With Matryoshka dimension reduction

```bash
curl -s https://api.jina.ai/v1/embeddings   -H "Content-Type: application/json"   -H "Authorization: Bearer $JINA_API_KEY"   -d '{
    "model": "jina-embeddings-v3",
    "input": ["بیمه نامه شخص ثالث چیست؟"],
    "task": "retrieval.query",
    "dimensions": 512
  }' | python3 -c "import sys,json; d=json.load(sys.stdin); print(f'dims={len(d["data"][0]["embedding"])}')"
```

**Key differences from OpenAI**:
- Use `task: "retrieval.query"` for queries, `task: "retrieval.passage"` for chunks
- Optional `dimensions` param for Matryoshka truncation
- Optional `late_chunking: true` for late-interaction-style results

**Response shape**: `data[0].embedding` = float array, `usage.total_tokens` = token count

## API Test — Python

```python
from jina import Client

client = Client(api_key="YOUR_JINA_API_KEY")  # or uses JINA_API_KEY env var

result = client.embed(
    inputs=["بیمه نامه شخص ثالث چیست?"],
    model="jina-embeddings-v3",
    task="retrieval.query"
)

embedding = result.embeddings[0].embedding
print(f"Dimensions: {len(embedding)}")
```

## TODO

- [ ] Verify enterprise licensing terms for local model (CC-BY-NC)
- [ ] Test cloud API with 100-question eval set
- [ ] Benchmark on MIRACL-Farsi subset
- [ ] Compare with OpenAI and Cohere on Farsi queries