OpenAI-compatible without the Azure overhead

Why teams switch from Azure OpenAI

Azure OpenAI customers commonly hit three walls: capacity quotas (provisioned throughput is limited and regional), model availability (not every model in every region), and cost structure (per-token plus provisioning). Plugsky removes all three: no quotas, 30+ models on one key, flat pricing.

Azure OpenAI vs Plugsky

	Azure OpenAI	Plugsky
API style	OpenAI-compatible (mostly)	OpenAI-compatible (same)
Capacity	Quotas, provisioning, regional limits	No quotas on plans
Models	OpenAI models only	30+ open-weight models
Failover	You build it	Automatic cascade
Residency	Azure regions	In-region, VPC, or on-prem

Migration path

1. Point your existing OpenAI SDK at https://api.plugsky.com/v1 — your Azure OpenAI code is already OpenAI-shaped.
2. Swap model names: gpt-4o → plugsky-pro, gpt-4o-mini → plugsky-lite, embeddings → plugsky-embed.
3. Test with the $5 trial; compare quality, latency, and cost.
4. Move environments one by one.

When Azure OpenAI is the better choice

If you need OpenAI's specific models under an existing Microsoft enterprise agreement, or your compliance posture requires Microsoft's certifications, Azure may be the right call. Plugsky is the alternative when quotas and lock-in are the problem — or when you want open-weight models and true sovereignty.

FAQ

Is the switch really one line?

For code using the OpenAI SDK — yes: change base_url and model names. See the OpenAI switch guide.

Do you offer enterprise agreements?

Yes — see enterprise.

What about data residency?

Choose in-region, VPC, or on-prem. See data residency.