How is Azure OpenAI Text Embedding 3 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.

Is Azure OpenAI Text Embedding 3 Small a chat model?

No—Azure OpenAI Text Embedding 3 Small is categorized as a embedding model. Use the matching API surface rather than assuming chat completions.

What is the context length for Azure OpenAI Text Embedding 3 Small?

Reported context for Azure OpenAI Text Embedding 3 Small is 8K tokens. Always verify the active provider row if multiple providers are listed.

What modalities does Azure OpenAI Text Embedding 3 Small support?

Azure OpenAI Text Embedding 3 Small accepts text and produces embedding according to its architecture metadata on LLM.API.

Does Azure OpenAI Text Embedding 3 Small support streaming?

Streaming depends on the active provider; check the providers table on this page for flags.

Where is the canonical page for Azure OpenAI Text Embedding 3 Small?

https://llmapi.ai/models/azure-text-embedding-3-small/

What are limitations of Azure OpenAI Text Embedding 3 Small?

Like other API models, Azure OpenAI Text Embedding 3 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.

Azure OpenAI Text Embedding 3 Small

Up to 30%

Azure OpenAI Text Embedding 3 Small delivers OpenAI embeddings through LLM.API so retrieval stacks stay simple and portable.

Start Using API

What is Azure OpenAI Text Embedding 3 Small?

Azure OpenAI Text Embedding 3 Small is an embedding model on LLM.API (`azure/text-embedding-3-small`). Azure-hosted OpenAI text-embedding-3-small. Provisional: requires the Azure deployment to be named exactly `text-embedding-3-small` until ProviderKeyOptions.AzureDeploymentType plumbing lands for embeddings. 1536-dim default, Matryoshka shrinkable. It maps text into embedding vectors for retrieval, clustering, and semantic search—not for chat completions.

Providers

LLM.API routes Azure OpenAI Text Embedding 3 Small to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput

azure$20 in

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

Provider	Pricing	Context	Capabilities
azure30% off	in $20.00/1M	8K tokens	—

Try this model

Test Azure OpenAI Text Embedding 3 Small right here — free to start.

Azure OpenAI Text Embedding 3 Small

Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Azure OpenAI Text Embedding 3 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="azure/text-embedding-3-small",
    input="Semantic search starts with strong embeddings.",
)
print(len(resp.data[0].embedding))

{
  "model": "azure/text-embedding-3-small",
  "input": "Semantic search starts with strong embeddings."
}

5 Core Capabilities

Cross-document matching
Supports near-duplicate detection and topical grouping. Tuned to how teams typically call Azure OpenAI Text Embedding 3 Small.
Low-latency lookups
Suitable for online retrieval when paired with a vector store. Reflects OpenAI 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. Reflects OpenAI positioning for this endpoint.
Corpus analytics
Enables semantic exploration of knowledge bases and tickets.

6 Most Valuable Use Cases

Recommendation features based on text similarity with Azure OpenAI Text Embedding 3 Small
Duplicate and near-duplicate content detection
Lead and account similarity scoring from notes with Azure OpenAI Text Embedding 3 Small
Multilingual document matching in one index
Anomaly grouping in incident descriptions with Azure OpenAI Text Embedding 3 Small
Semantic search over docs, tickets, and wikis

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 Azure OpenAI Text Embedding 3 Small on LLM.API?

Unified AI Routing
Practical: Reach Azure OpenAI Text Embedding 3 Small and sibling models through one OpenAI-compatible endpoint.
Cost Control
Compare provider price points and keep spend visible as you scale Azure OpenAI Text Embedding 3 Small.
Reliability Layer
Retry and route across configured providers when a single upstream blips.
Observability
Trace prompts, tokens, and errors for Azure OpenAI Text Embedding 3 Small alongside the rest of your stack.
Drop-in SDKs
Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Model Breadth
Production: Swap Azure OpenAI Text Embedding 3 Small for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

You are building search, RAG, or clustering on text (Azure OpenAI Text Embedding 3 Small)
Throughput and cost matter more than generative prose quality (Azure OpenAI Text Embedding 3 Small)
You need consistent vectors from an OpenAI-compatible embeddings API (Azure OpenAI Text Embedding 3 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

RELIABILITY