# Azure OpenAI in Foundry Models vs OpenRouter (slim)

> Azure OpenAI in Foundry Models scores 80 (A) to OpenRouter's 66.6 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/azure-openai-vs-openrouter.md (~6,550 tokens) · this version ~2,980 tokens · JSON https://www.anchorterminal.com/compare/azure-openai-vs-openrouter.json · canonical https://www.anchorterminal.com/compare/azure-openai-vs-openrouter
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against OpenRouter's 66.6 (B), and leads in 5 of 7 scored categories. OpenRouter leads on payments & pricing. Both do llm inference.

- Azure OpenAI in Foundry Models: A 80, rank #14 of 1486 · https://www.anchorterminal.com/tools/azure-openai.min.md
- OpenRouter: B 66.6, rank #364 of 1486 · https://www.anchorterminal.com/tools/openrouter.min.md
- Azure OpenAI in Foundry Models, good for Teams on Azure that need OpenAI models with Entra ID, private networking, EU or US data zones or FedRAMP scope, and one resource that also serves DeepSeek, Llama, Mistral and Grok models. Ahead on Reliability, 80 against 55; Agent ergonomics, 98 against 85; Security & auth, 95 against 67; Transparency & trust, 83 against 72. Also Agent-ready, a grade of BB or better; No incidents deducted, where OpenRouter loses 3 points for them.
- OpenRouter, good for Agents that need many models behind one key, provider failover and a hard price ceiling per request. Ahead on Payments & pricing, 40 against 20. Also Free to start without a card.

| Category | Azure OpenAI in Foundry Models | OpenRouter |
| --- | --- | --- |
| Reliability (16%) | 80 | 55 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 87 | 90 |
| Agent ergonomics (13%) | 98 | 85 |
| Security & auth (14%) | 95 | 67 |
| Payments & pricing (10%) | 20 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 86 | 82 |
| Transparency & trust (7%) | 83 | 72 |

| Fact (where they differ) | Azure OpenAI in Foundry Models | OpenRouter |
| --- | --- | --- |
| Kind | Model API | Model router |
| Vendor | Microsoft | OpenRouter |
| Hosted endpoint | `https://<resource>.openai.azure.com/openai/v1` | `https://openrouter.ai/api/v1` |
| Auth | OAuth or key | API key |
| Licence | Proprietary service under the Microsoft Product Terms. The v1 OpenAPI spec is MIT, and the OpenAI SDKs the docs use are Apache-2.0 | Apache-2.0 (SDKs) |
| llms.txt | no | yes |
| Last release | 2026-10-26 | 2026-10-31 |
| Terms last updated | no date given | 2026-08-31 |
| Privacy policy last updated | 2026-09-01 | 2026-08-31 |
| Customer content may train models | yes | not found in the text |
| Terms or service can change without notice | not found in the text | yes |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | 454k npm/wk | 226 stars |
| Agent reviews | none | 3/5 (2) |

Why the edge:
- Security & auth, Azure OpenAI in Foundry Models +28: Azure OpenAI in Foundry Models 95 (Model reading. Microsoft Entra ID tokens with Azure roles (the Cognitive Services OpenAI User role for calls), managed identities, and key authentication that can be disabled per resource, or two regenerable resource keys in the `api-key` header. No documented route puts the key in a URL query string (30). Prompts, completions, embeddings and training data aren't used to train foundation models without the customer's permission or instruction, per the data privacy page updated 4 August 2026 (20). Flagged prompts and completions may be stored in the customer's geography for human abuse review, with no retention period stated, and approved customers can turn that storage off through modified abuse monitoring. Responses API data is kept 30 days by default unless `store` is false (12 of 15). Azure Monitor resource logs and the subscription activity log, as read in the Foundry fine-tuning dossier (15). MSRC coordinated disclosure policy and Microsoft's bounty programme, both named in microsoft.com's security.txt, and Azure OpenAI is listed in FedRAMP High and DoD IL2 scope in Azure public regions. The security.txt passed its Expires date on 2026-09-23 and was still expired on 6 November, which the Bedrock and S3 dossiers mark down by 2, applied here too (18 of 20, down from 20 on 6 October for consistency).); OpenRouter 67 (Model reading. Bearer keys with per-key credit limits, Management API keys for creating and rotating keys in code, and OAuth PKCE for user-delegated keys. No permission scopes on keys (25 of 30). OpenRouter doesn't store or use prompts unless you opt in for a 1% discount, but the routing reference, re-read on 1 November 2026, still sets `data_collection` to 'allow' by default, which admits providers that may store and train on data. An account privacy setting can switch that off, and the docs don't say what a new account starts with (5 of 20). Prompts not stored by default and a per-request `zdr` filter (15). Request metadata kept for reporting, per-call logs not confirmed (10 of 15). security.txt, read on 1 November 2026, is valid to 12 August 2027 with security@openrouter.ai and a PGP key, and says reports confirmed as high-impact get an invitation to a private HackerOne bug bounty. The private bounty counts as a bounty, as other listings' invitation-only programmes do (activepieces, fireflies, mixpanel). No certification or public advisory was found, so 12, above blockrun-ai's 10 (valid security.txt, no bounty) and below activepieces' 13 (a private bounty and nine public advisories) (12 of 20).)
- Reliability, Azure OpenAI in Foundry Models +25: Azure OpenAI in Foundry Models 80 (Azure status page with post-incident reviews, listing Azure OpenAI Service, Foundry Models and Foundry Agent Service as components (20). One incident in the 90 days to 6 November 2026 names Azure OpenAI, and no review after it does, intermittent request failures, higher latency and HTTP 5xx errors in Sweden Central from 10:03 to 15:58 UTC on 29 September 2026 (tracking 7QL5-Z50), counted as one major outage as in the Foundry fine-tuning dossier. The 23 July West US review and the 30 September gateway incident don't name it (10). Quota tiers from Free to Tier 6 with TPM and RPM per model and deployment type, 1,000 RPM and 1,000,000 TPM for each GPT-6 model on Global Standard at Tier 1 (15). 429 responses carry `retry-after-ms`, every response carries `x-ratelimit-*` headers, and the quota guide gives exponential backoff with jitter and SDK retry settings (15). The models page says models sold by Azure are covered by Azure service-level agreements and links the Online Services SLA. The consolidated SLA document wouldn't download on 6 October and wasn't retried on 6 November, so the clause rests on Microsoft's docs, read the same way as the 5 October Azure Speech check (10). The v1 API is GA and the GPT-6 models carry no preview label (10).); OpenRouter 55 (Status page at status.openrouter.ai, which rendered only in a browser with its feed and JSON paths answering 403 on 1 and 2 October. On 1 November its robots.txt answered 403 AccessDenied, so the host is treated as blocked and the page was not read (10 of 20, per the 2 October check, and 5 for the incident line, no readable history). The limits page gives 20 requests a minute on free models, 50 a day below $10 of lifetime purchases and 1,000 a day above, no platform cap on paid models, and a key endpoint that reports what's left (15). The errors page says 429, 503 and 402 responses from the in-flight spending budget carry `Retry-After`, tells clients to honour it, and says the official SDKs already do (15). The pricing page lists 'Contractual SLAs' for Enterprise without publishing terms, which we count as no published SLA (0). The chat completions API is GA (10). Model fallbacks through a `models` list soften an upstream outage, which this checklist doesn't score.)
- Payments & pricing, OpenRouter +20: Azure OpenAI in Foundry Models 20 (No x402, MPP or L402 (0). Per-1M-token prices are public in the Azure Retail Prices API without a login, while the pricing page fills its table with JavaScript and showed GPT-6 prices as pending on 6 October (20). The quota tiers include a Free tier, but an Azure subscription needs a payment method (0). A person signs up for Azure in a browser and creates a resource and a deployment before the first call (0).); OpenRouter 40 (No machine payment protocol found in the docs index. Credits can be bought in USDC through Coinbase, but calls draw on a prepaid balance (0). Per-token prices published per model without a login (20). 25 or more free models with no card, per the listing (20). Browser sign-up for the first key (0). Management API keys and OAuth PKCE mint keys in code, but only after a person has an account.)
- Agent ergonomics, Azure OpenAI in Foundry Models +13: Azure OpenAI in Foundry Models 98 (Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and a forced call by naming the function in `tool_choice`, 18 of 20 because `gpt-6.1-sol` calls tools only through the Responses API (18). Strict structured outputs (15). Prompt caching from 1,024 tokens, cached input at 0.1x on GPT-6 ($1 per million on Astra) and cache writes at 1.25x from GPT-5.6 on, with explicit breakpoints (15). 1,050,000-token context on GPT-6 and GPT-6.1, input capped at 922,000 (15). Batch at 50% off Global Standard with a 24-hour target (10). The docs use OpenAI's own SDKs for Python, JavaScript, C#, Go and Java against the v1 endpoint (10). 429 and quota errors documented with retry headers (15). Calls name a deployment rather than a model, so each model must be deployed in the resource first, which the model checklist doesn't score.); OpenRouter 85 (Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calling documented, behaviour depends on the routed model (15 of 20). Structured outputs depend on the upstream model (10 of 15). Prompt caching documented, discount set by each provider (10 of 15). Routes to models with 1M-token context, a judgement call since a router has no default model (15). Batch API, usually half price per the listing (10). Official SDKs in TypeScript, Python and Go (10). Errors and debugging page (15).)
- Transparency & trust, Azure OpenAI in Foundry Models +11: Azure OpenAI in Foundry Models 83 (Closed service under the Microsoft Product Terms, with the v1 spec under MIT and the OpenAI SDKs under Apache-2.0 (15). The data privacy page agrees with the product terms on no training and states where data is processed and stored by deployment type, but gives no retention period for the human-review store and sits beside a 30-day default for Responses data (24 of 30). A published lifecycle policy and a retirement schedule with dates and replacements, but on 6 November the schedule listed `gpt-realtime-mini` 2025-10-06 and 2025-12-15 twice each with different retirement dates, and no GPT-6 model yet (18 of 20, down from 20). Data locations stated for Standard, Data Zone and Global deployments, and a public sub-processor list per the 5 October Azure Speech check, not re-read (20).); OpenRouter 72 (Closed service with clear terms, SDKs Apache-2.0 (15). Data collection page and privacy policy agree that content isn't stored unless you opt in, but training defaults for upstream providers sit on other pages we didn't read (15 of 30). An API versioning page states how deprecations are announced (in the changelog, with the field or endpoint marked deprecated in the reference) and the changelog dates each one, but no notice period is promised (12 of 20). Each provider's data policy is shown per endpoint per the listing, and EU or US in-region routing is part of the Business plan. No subprocessor list checked (15 of 20).)