How much does Azure OpenAI text-embedding-3-small cost?

Azure OpenAI text-embedding-3-small costs $0.02 per million tokens on pay-as-you-go (standard) pricing, matching OpenAI direct as of the verification date on this page. Provisioned Throughput Units (PTUs) offer a discount in exchange for reserved capacity and a minimum monthly commitment.

Does Azure OpenAI offer the Batch API discount on embeddings?

No. As of 2026 the 50% Batch API discount available on OpenAI direct is not offered for embedding models on Azure OpenAI. This is the single biggest pricing difference between the two platforms. Bulk indexing workloads see a meaningful cost premium on Azure unless they qualify for PTU reserved-capacity pricing.

Which Azure regions support text-embedding-3-small and text-embedding-3-large?

Embedding model availability varies by region and changes regularly. East US, East US 2, North Central US, South Central US, West Europe, and Sweden Central typically lead in availability. UK South and Australia East follow. Always check the live Azure model availability page before architecting a deployment - regional gaps cause real engineering pain when discovered after the fact.

Does Azure OpenAI charge for data egress?

Azure OpenAI itself charges per token, with no separate egress fee for API responses. However, if your embedding service sits behind a VNet and traffic routes through Private Endpoints or Azure Firewall, those services have their own per-GB costs that apply to the response payload (which is small for embeddings - typically 6KB per vector at 1536 dimensions in float32). Self-hosted vector databases pulling embeddings across regions also incur standard Azure inter-region transfer fees.

Is Azure OpenAI cheaper than OpenAI direct for embeddings?

Per-token pay-as-you-go pricing is identical between the two as of 2026. OpenAI direct is cheaper in absolute terms because of the 50% Batch API discount, which Azure does not offer. Azure becomes cheaper only if you commit to PTUs and run high consistent volume. For most teams under 1 billion tokens per month, OpenAI direct on the Batch API is the lowest-cost option.

Does Azure OpenAI support Matryoshka dimension truncation for text-embedding-3-large?

Yes. The 'dimensions' parameter that lets you request 1536-dimension output from text-embedding-3-large (instead of the default 3072) works identically on Azure. The per-token price is unchanged but you halve your downstream storage cost. Quality loss is minimal - 1-2 MTEB points.

What is the deployment model for Azure OpenAI embeddings?

You deploy each embedding model as a 'deployment' within an Azure OpenAI resource. Each deployment has its own endpoint URL and capacity allocation. You can create multiple deployments of the same model to isolate workloads, apply different rate limits, or split costs across cost centres. Deployments are free to create - you only pay for tokens consumed.

Azure OpenAI Embedding Pricing 2026 (May 2026)

Per-token pricing for text-embedding-3-small, 3-large, and ada-002 on Azure OpenAI Service, plus how PTU reserved capacity changes the math and the key differences against OpenAI direct.

Verified May 2026

Current Pricing (Pay-As-You-Go)

Model	Standard $/M	Batch $/M	Dims	MTEB
text-embedding-3-small Recommended	$0.02	not offered	1536	62.3
text-embedding-3-large High accuracy	$0.13	not offered	3072	64.6
text-embedding-ada-002 Legacy - migrate	$0.10	not offered	1536	60.5

Pay-as-you-go rates verified May 2026. The Batch API 50% discount available on OpenAI direct is not offered on Azure OpenAI for embedding models.

Cost at scale (pay-as-you-go)

Model	100M tokens	1B tokens	10B tokens
text-embedding-3-small	$2	$20	$200
text-embedding-3-large	$13	$130	$1,300
text-embedding-ada-002	$10	$100	$1,000

Provisioned Throughput Units (PTUs)

PTUs are Azure's reserved-capacity pricing model. You commit to a fixed throughput allocation for a monthly or annual term in exchange for predictable pricing, guaranteed capacity, and protection against pay-as-you-go list-price changes.

Embedding workloads typically need fewer PTUs than chat-completion workloads because embedding requests are short and high-throughput. The exact discount versus pay-as-you-go depends on region, term length, and any Enterprise Agreement-level negotiation. Public list reference points have historically broken even with pay-as-you-go at roughly 200-300 million tokens per month for embeddings, but Microsoft does not publish a single canonical PTU price for embeddings, so you must request a quote.

When PTU makes sense: sustained high-throughput indexing (catalogue ingestion, search-index refresh), latency-sensitive online retrieval that needs guaranteed capacity, or regulated workloads where pay-as-you-go variance is a procurement blocker. For variable or bursty workloads, pay-as-you-go is almost always cheaper.

Azure OpenAI versus OpenAI direct: key differences

Aspect	OpenAI direct	Azure OpenAI
Pay-as-you-go $/M tokens	$0.02 - $0.13	$0.02 - $0.13 (matches)
Batch API 50% discount	Yes	No
Reserved capacity	Not offered for embeddings	PTU (monthly / annual term)
Regional control	Global only	25+ regions, data residency
Enterprise compliance	SOC 2, GDPR	SOC 2, GDPR, HIPAA, FedRAMP, more via inheritance
Private networking	Public endpoint only	Private Endpoints, VNet
Volume discounts	Limited (Enterprise tier)	EA-level discounts on Azure commit

Choosing between Azure and OpenAI direct

Pick OpenAI direct if your workload is mostly bulk indexing (Batch API saves 50%), you have no data-residency requirement, and you want the lowest absolute cost.

Pick Azure OpenAI if you need EU / UK / US data residency, you are already on an Azure Enterprise Agreement (committed Azure spend reduces effective embedding cost), you need Private Endpoints / VNet, or you require HIPAA / FedRAMP compliance.

Pick Azure PTU if you have sustained, predictable embedding throughput above roughly 200-300 million tokens per month and your latency requirements rule out the Batch API anyway. Get a Microsoft account team quote before assuming PTU is cheaper - the answer is region- and term-dependent.

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