Bonus: Top up now and we'll double your first deposit — get x2 credits instantly.
Get Started
Sign Up
Sign Up

Jina Embeddings v5 Text Small

Up to 30%

Jina Embeddings v5 Text Small delivers Jina embeddings through LLM.API so retrieval stacks stay simple and portable.

Start Using API

What is Jina Embeddings v5 Text Small?

Jina Embeddings v5 Text Small is an embedding model on LLM.API (`jina-embeddings-v5-text-small`). Jina's SOTA small multilingual text embedding model. 1024 default dimensions (Matryoshka, truncatable to 32); 32K context. It maps text into embedding vectors for retrieval, clustering, and semantic search—not for chat completions.

Providers

LLM.API routes Jina Embeddings v5 Text Small to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
jina$0.02 in
$0 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
jina30% offin $20; out $0 per 1M tokens33K tokens—

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Jina Embeddings v5 Text Small right here — free to start.

Jina Embeddings v5 Text Small
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Jina Embeddings v5 Text Small through the OpenAI-compatible API — POST /v1/embeddings.

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.embeddings.create(
    model="jina-embeddings-v5-text-small",
    input="Semantic search starts with strong embeddings.",
)
print(len(resp.data[0].embedding))
{
  "model": "jina-embeddings-v5-text-small",
  "input": "Semantic search starts with strong embeddings."
}

5 Core Capabilities

  • Classification features

    Vectors can feed lightweight classifiers and routing logic.

  • Cross-document matching

    Supports near-duplicate detection and topical grouping. Reflects Jina positioning for this endpoint.

  • Semantic vectorization

    Maps text into dense vectors for similarity search and clustering. Grounded in the model's embedding role rather than generic chat claims.

  • Batch throughput

    Designed for embedding large corpora via the OpenAI-compatible API. Relevant for `jina-embeddings-v5-text-small` workloads on LLM.API.

  • Multilingual text

    Embeds content across languages depending on the underlying model family. Reflects Jina positioning for this endpoint.

6 Most Valuable Use Cases

  • Recommendation features based on text similarity with Jina Embeddings v5 Text Small
  • Anomaly grouping in incident descriptions
  • Duplicate and near-duplicate content detection with Jina Embeddings v5 Text Small
  • Topic clustering for content and support queues
  • Semantic search over docs, tickets, and wikis with Jina Embeddings v5 Text Small
  • Lead and account similarity scoring from notes

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Jina Embeddings v5 Text Small on LLM.API?

  • Unified AI Routing

    Reach Jina Embeddings v5 Text Small and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Production: Compare provider price points and keep spend visible as you scale Jina Embeddings v5 Text Small.

  • Reliability Layer

    Retry and route across configured providers when a single upstream blips.

  • Observability

    Trace prompts, tokens, and errors for Jina Embeddings v5 Text Small alongside the rest of your stack.

  • Drop-in SDKs

    Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Production: Swap Jina Embeddings v5 Text Small for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You need consistent vectors from an OpenAI-compatible embeddings API (Jina Embeddings v5 Text Small)
  • Throughput and cost matter more than generative prose quality (Jina Embeddings v5 Text Small)
  • You are building search, RAG, or clustering on text (Jina Embeddings v5 Text Small)

Avoid if...

  • You only need OCR or speech features
  • You require cross-model vector compatibility without re-indexing
  • You need generative answers instead of vectors

COMMUNITY

What developers say about embedding models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Jina Embeddings v5 Text Small.

  • Side-by-side scoring puts OpenAI embeddings slightly ahead of Cohere overall, largely on ecosystem and community support.
  • Cost comparisons favour usage-based OpenAI pricing for small and mid-sized workloads.
  • Retrieval quality differences are workload-specific; reviewers recommend evaluating on your own corpus before committing.

SOURCES

Frequently Asked Questions

  • Can Jina Embeddings v5 Text Small generate paragraphs of text?

    No. Jina Embeddings v5 Text Small returns embeddings (vectors). Pair it with a chat model if you need generated language.

  • Where is the canonical page for Jina Embeddings v5 Text Small?

    https://llmapi.ai/models/jina-embeddings-v5-text-small/

  • Is Jina Embeddings v5 Text Small a chat model?

    No—Jina Embeddings v5 Text Small is categorized as a embedding model. Use the matching API surface rather than assuming chat completions.

  • When should I choose Jina Embeddings v5 Text Small?

    You need consistent vectors from an OpenAI-compatible embeddings API — especially when you specifically need Jina Embeddings v5 Text Small.

  • What are limitations of Jina Embeddings v5 Text Small?

    Like other API models, Jina Embeddings v5 Text Small can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

  • How is Jina Embeddings v5 Text Small priced on LLM.API?

    Listed pricing metadata shows: In $0.02 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • What is Jina Embeddings v5 Text Small?

    Jina's SOTA small multilingual text embedding model. 1024 default dimensions (Matryoshka, truncatable to 32); 32K context. On LLM.API it is addressed as `jina-embeddings-v5-text-small`.

  • Which providers serve Jina Embeddings v5 Text Small?

    LLM.API currently lists: jina. Availability can vary by region and account.

  • What is the context length for Jina Embeddings v5 Text Small?

    Reported context for Jina Embeddings v5 Text Small is 33K tokens. Always verify the active provider row if multiple providers are listed.

COMPARE

Competitive Models

Get one key to every model

Swap your API key. Keep your code.

Start for free Talk to sales