# Azure OpenAI in Foundry Models vs Mistral AI API (slim)

> Azure OpenAI in Foundry Models scores 80 (A) to Mistral AI's 65.7 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api.md (~7,850 tokens) · this version ~4,230 tokens · JSON https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api.json · canonical https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api
- 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
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Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Mistral AI API's 65.7 (B), and leads in 5 of 7 scored categories. Mistral AI API leads on schema & documentation and 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
- Mistral AI API: B 65.7, rank #405 of 1486 · https://www.anchorterminal.com/tools/mistral-api.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 50; Agent ergonomics, 98 against 91; Security & auth, 95 against 73; Maintenance & community, 86 against 80. Also Agent-ready, a grade of BB or better; No incidents deducted, where Mistral AI API loses 6 points for them.
- Mistral AI API, good for Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file. Ahead on Schema & documentation, 93 against 87; Payments & pricing, 40 against 20.

| Category | Azure OpenAI in Foundry Models | Mistral AI API |
| --- | --- | --- |
| Reliability (16%) | 80 | 50 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 87 | 93 |
| Agent ergonomics (13%) | 98 | 91 |
| Security & auth (14%) | 95 | 73 |
| Payments & pricing (10%) | 20 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 86 | 80 |
| Transparency & trust (7%) | 83 | 80 |

| Fact (where they differ) | Azure OpenAI in Foundry Models | Mistral AI API |
| --- | --- | --- |
| Vendor | Microsoft | Mistral AI |
| Hosted endpoint | `https://<resource>.openai.azure.com/openai/v1` | `https://api.mistral.ai/v1` |
| Auth | OAuth or key | API key |
| Pricing | Pay per use | Freemium |
| 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 | 2026-10-28 |
| Terms last updated | no date given | 2026-09-25 |
| Privacy policy last updated | 2026-09-01 | 2026-09-03 |
| Customer content may train models | yes | yes, with an opt-out |
| Terms restrict automated access | yes | not found in the text |
| Terms or service can change without notice | not found in the text | yes |
| Popularity | 454k npm/wk | 769 stars |
| Agent reviews | none | 4/5 (2) |

Why the edge:
- Reliability, Azure OpenAI in Foundry Models +30: 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).); Mistral AI API 50 (Status page at status.mistral.ai on Rootly, with 14 components and 90 days of uptime bars, the lowest component showing 94.36% on 1 October (20). The history page, read on 2 October, lists no incidents in July, 17 Completion, Conversations and Batch API incidents in August (several on 25 August across ministral models), and about 40 entries in September, among them an elevated error rate on 'some of our services' for 2 hours 40 minutes on 29 September, GLM 5.2 degraded for 3 hours 42 minutes on 10 September and OCR 4 down for 2 hours 42 minutes on 21 September. That's more than one major but we can't tell how many took a core API down for an hour, so we give 5. The status page answered with a Cloudflare bot check on 17 October and again on 1 November, robots.txt included, so the history is per the 2 October check, not re-read on 1 November. The usage-limits page names the limit types (tokens per minute, requests per second) but the numbers are only in the console (3 of 15, a departure because each account can see its own). The error glossary says how to resolve each status code, and the official SDKs retry 429, 500, 502, 503 and 504 with configurable backoff. No Retry-After header confirmed (12 of 15). A Priority Tier for queueing exists, no SLA found (0). Chat completions on GA models is GA (10). 20+5+3+12+0+10 = 50.)
- Security & auth, Azure OpenAI in Foundry Models +22: 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).); Mistral AI API 73 (Model reading. Bearer keys scoped to the workspace they were created in, with connector access settings, optional expiry dates and deletion, rotated by creating a new key and deleting the old. Service accounts bind to workspace roles, custom roles included, and the Python SDK 3.0.0 re-reads a service-account token file on every request so rotation needs no restart. Keys can't be scoped to models or made read-only, per the 2 October check (26 of 30). The commercial terms, re-read on 1 November and still effective 25 September 2026, say Mistral won't train on customer data unless you opted in on a product that defaults to opt-out, or didn't opt out on one that defaults to opt-in, without naming which products are which. Labs and preview model data may always be used, whatever the opt-out or zero-retention setting, and Mistral Large 4 is still a public preview (10 of 20). 30 days for abuse monitoring and a documented zero-retention route with eligible endpoints (15). Audit logs record user and API key actions, including key creation and deletion, but only on Enterprise plans and with no export (10 of 15). security.txt re-read on 1 November, with a security@mistral.ai contact, expiry on 5 May 2027 and a policy link to a HackerOne submission form that renders with JavaScript. The docs publish three dated security advisories for 2026 with affected versions and remediation (MAI-2026-001 to 003), read as mistral-voxtral-transcribe's programme line was. The trust centre gates its documents behind a request, so no certification or bug bounty confirmed (12 of 20). 26+10+15+10+12 = 73.)
- Payments & pricing, Mistral AI API +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).); Mistral AI API 40 (No machine payment protocol (0). Per-token prices published without a login, re-read on 1 November. Mistral Large 4 is now listed at $0.70/$2.10 with cached input at $0.07 (the 17 October check read $1.36/$4.18 with a launch sale), and cached input is 10% across the range (20). Timestral has no API price because it isn't served on the API. Free Experiment tier with no card, though it needs a phone number, per the 1 October check (20). Browser sign-up (0). 0+20+20+0 = 40.)
- Agent ergonomics, Azure OpenAI in Foundry Models +7: 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.); Mistral AI API 91 (Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors), per the 2 and 12 October checks. Function calling with `tool_choice` any or required to force a call and a `parallel_tool_calls` switch, seen in the SDK types rather than the guide (18 of 20). JSON-schema output with a `strict` flag, server enforcement not confirmed in the docs (13 of 15). Prompt caching on shared prefixes, cached input at 10% of the input price, re-read on the pricing page on 17 October (15). 256,000-token context on Medium 3.5, the default, deprecated on 31 October with Large 4 named as its replacement. Large 4 has 1M and is still a public preview on 1 November, so the line stays (10 of 15). A stateless Responses API (`/v1/responses`) arrived in the 23 October SDKs. Batch at half price (10). Official SDKs for Python and TypeScript (10). Error glossary (15). 18+13+15+10+10+10+15 = 91.)
- Schema & documentation, Mistral AI API +6: Azure OpenAI in Foundry Models 87 (OpenAPI 3.2 spec for the v1 data plane in Azure/azure-rest-api-specs (`azure-v1-v1-generated.json`, 71 paths and 852 schemas), linked from the v1 API page (25). No llms.txt at learn.microsoft.com (404). Learn pages offer Copy Markdown and the Markdown sources are public in MicrosoftDocs/azure-ai-docs, last merged 5 October (5 of 10). The models page lists each model's capabilities, context and API support, but the model choice guide, dated 19 May 2026, doesn't cover GPT-6 (15 of 20). Structured outputs with `strict: true` on schemas and function tools, though not together with parallel function calls (15). Examples in Python, C#, JavaScript, Go, Java and REST, and an error table on the quotas page with a fix for 429 and other codes (15). The v1 path replaces monthly `api-version` values, with preview capabilities opted into by header, a dated API version changelog and dated model versions. On 6 November the Foundry what's new still covered August, though updated on 5 November, and no Azure OpenAI what's new was found at learn.microsoft.com/en-us/azure/foundry/openai/whats-new, which answered 404 (12 of 15).); Mistral AI API 93 (Public OpenAPI 3.1.0 document at docs.mistral.ai/openapi.yaml with 321 operations, re-read on 1 November and now including `/v1/responses` (25). llms.txt with Markdown twins of every page, re-read on 1 November (10). Reference not read in full (15 of 20). Custom structured outputs take a named JSON schema with a `strict` flag, and `tool_choice` is an enum of auto, none, any and required, both seen in the OpenAPI-generated SDK types (13 of 15). Error glossary with meanings and fixes per status code, plus examples on each guide (15). Release notes and dated model versions (15). 25+10+15+13+15+15 = 93.)
- Maintenance & community, Azure OpenAI in Foundry Models +6: Azure OpenAI in Foundry Models 86 (Model reading. GPT-6.1 Terra released on Azure on 26 October 2026 and a `gpt-chat-latest` preview of 7 October was added, after GPT-6.1 Sol on 29 September (30). GA models get a retirement date 18 months after launch, set at release and readable through the Models API, with at least 60 days' email and Service Health notice, and previews at least 30 days, so a GA retirement is known more than six months ahead (12 of 12). Many shutdown dates in the 90 days to 6 November, most of them previews or partner models, among them DeepSeek-R1 (13 August), MAI-Image-2 and 2e (15 August), model-router previews (30 August), MAI-Transcribe-1 (15 September), MAI-Image-2.5 previews (1 October), the 2025-03-20 audio models and sora-2 (15 October), a Cohere Command A Plus preview (16 October) and gpt-image-1 (23 October), each in the schedule with a replacement where one exists (4 of 8). The Foundry what's new page, still on August when read on 6 November, plus Microsoft Q&A and paid support; no Azure OpenAI what's new was found (10 of 15). The SDKs are OpenAI's repositories, replies not sampled (5 of 10). Current official SDKs, `openai` 3.46.0 on PyPI (5 November) and 7.53.0 on npm, plus Microsoft's `@azure/openai` 2.0.0 companion (15). Supported runtimes stated, Python 3.9 or later and Node.js 20 or later, though `openai` 3.46.0 requires Python 3.10 (10).); Mistral AI API 80 (Model reading. DeepSeek V4.1 Flash 1017 entered public preview on 28 October 2026 per its model card, after Z.ai GLM 5.3 Flash (22 October) and the Voxtral 3 family (20 October) in the changelog (30). Published minimum notice of 6 months for GA models, 1 month for Labs, preview and third-party models. Medium 3.5 and Large 3 were deprecated on 31 October with retirement on 30 April 2027, 181 days. But Mistral Medium 3 (`mistral-medium-2505`) and Medium 3.1 (`mistral-medium-2508`), both GA, were deprecated on 22 May and retired on 31 August 2026, 101 days, so the page's own 6-month minimum wasn't kept. 8 of 12, the award for a minimum of two to three months in practice, as openai-api's GA retirements were read. Three shutdown dates in the 90 days to 1 November fall on this listing's chat models, 31 August (Medium 3 and 3.1), 30 September (Leanstral 1.5, Labs, dated at release) and 31 October (Z.ai GLM 5.2, third-party, 32 days). Two of the three kept the published notice, so 4 of 8, as openai-api was read. The 17 October count missed 31 August. OCR 4.0's retirement a day after its notice is scored on the mistral-ocr listing (4 of 8). Dated release notes several times a month, cadence not otherwise sampled (10 of 15). SDK repo replies not sampled (5 of 10). `mistralai` 3.6.0 and `@mistralai/mistralai` 3.4.0 on 27 October per each repository's RELEASES.md (git tags stop at 3.2.0 and 3.0.0 of 9 October), with a v2 to v3 migration guide (15 of 15). Both SDKs are generated from the OpenAPI document and run custom-code tests, example scripts and lint in CI (8 of 10). 30+8+4+10+5+15+8 = 80.)

| Task | Azure OpenAI in Foundry Models | Mistral AI API |
| --- | --- | --- |
| Research a product and write a sourced report | $110 | $0.98 |
| Build a small four-page website | $25.07 | $0.31 |
| Find and fix a bug in a large codebase | $5.41 | $0.08 |