{ "data": { "a": { "slug": "azure-openai", "name": "Azure OpenAI in Foundry Models", "vendor": "Microsoft", "vendorUrl": "https://azure.microsoft.com", "kind": "model", "category": "inference", "summary": "Microsoft Azure's hosted API for OpenAI's GPT models and other Foundry Models sold by Azure, such as DeepSeek, Llama, Mistral and Grok, called through an OpenAI-compatible v1 endpoint on each customer's Azure resource.", "url": "https://www.anchorterminal.com/tools/azure-openai", "markdownUrl": "https://www.anchorterminal.com/tools/azure-openai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/azure-openai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/azure-openai.json", "dns": "azure-openai.grade.anchorterminal.com", "repo": "https://github.com/Azure/azure-rest-api-specs", "license": "Proprietary service under the Microsoft Product Terms. The v1 OpenAPI spec is MIT, and the OpenAI SDKs the docs use are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "packages": [ { "registry": "pypi", "name": "openai" }, { "registry": "npm", "name": "openai" }, { "registry": "npm", "name": "@azure/openai" } ], "auth": "mixed", "authNotes": "`api-key` header with one of the resource's two regenerable keys, or a Microsoft Entra ID bearer token (scope https://ai.azure.com/.default) with the Cognitive Services OpenAI User role. Key authentication can be disabled per resource (`disableLocalAuth`). Each model must be deployed in the resource before it can be called, by deployment name.", "pricing": "usage", "pricingNotes": "Pay per token on an Azure subscription. Global Standard GPT-6 and GPT-6.1 prices match OpenAI's list (GPT-6.1 Sol $2/$10, GPT-6.1 Terra $1/$5 per million tokens), Data Zone costs 10% more, long-context requests cost 2x input and 1.5x output, cached input 0.1x, cache writes 1.25x, Flex half price and priority processing 2x (GPT-6 Sol). Batch is 50% off Global Standard. Provisioned throughput is billed per PTU hour. Prices from the Azure Retail Prices API, because the pricing page fills its table with JavaScript (checked 2026-11-06).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Foundry docs, the v1 OpenAPI spec or the pricing page. Access needs an Azure subscription with a payment method (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 454039, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://learn.microsoft.com/en-us/azure/foundry/openai/", "rateLimitsUrl": "https://learn.microsoft.com/en-us/azure/foundry/openai/quotas-limits", "openapi": "https://github.com/Azure/azure-rest-api-specs/blob/main/specification/ai/data-plane/OpenAI.v1/azure-v1-v1-generated.json", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "card-required", "openapi", "openai-compatible", "closed-source", "enterprise", "eu", "python", "typescript", "status-page", "bug-bounty" ], "lastRelease": "2026-10-26", "graded": true, "anchor": { "graded": true, "score": 80, "grade": "A", "agentReady": true, "rank": 14, "ranked": true, "rankOf": 1486, "categoryRank": 4, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 98, "maintenance": 86, "payments": 20, "reliability": 80, "schema": 87, "security": 95, "transparency": 83 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.", "bestFor": "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.", "strengths": [ "Public OpenAPI 3.2 spec for the v1 API, 71 paths covering Responses, Chat Completions, batches, files and vector stores", "Microsoft Entra ID tokens with Azure roles, and key authentication can be switched off per resource", "GA models carry a retirement date 18 months after launch, set at release and readable through the Models API", "Data Zone deployments keep processing inside the EU or US, and Azure OpenAI is in FedRAMP High scope", "GPT-6 Astra, Sol and Luna at $10/$50, $2/$10 and $0.10/$0.50 per million tokens on Global Standard" ], "weaknesses": [ "Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026", "An Azure subscription with a card, a resource and a model deployment come before the first call", "No llms.txt, and no Azure OpenAI what's new page was found; the Foundry one still covered August on 6 November", "No retention period stated for prompts kept for human abuse review, and Responses data is kept 30 days by default", "The retirement schedule lists two `gpt-realtime-mini` versions twice with different retirement dates, and no GPT-6 retirement dates yet" ], "agentNotes": [ "Point the OpenAI SDK at https://\u003cresource\u003e.openai.azure.com/openai/v1/ and pass the deployment name as `model`, not the model id", "Prefer Entra ID with the Cognitive Services OpenAI User role over the resource key, which opens the whole data plane", "On 429 wait for `retry-after-ms`, then back off with jitter. The OpenAI SDK retries twice by default", "Set `store: false` on Responses calls you don't need kept. Stored responses persist 30 days by default", "Keep remote MCP approvals on for servers you don't control. They're required by default" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "A", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 80 } ], "editorialScores": { "ergonomics": 98, "maintenance": 86, "payments": 20, "reliability": 80, "schema": 87, "security": 95, "transparency": 77 }, "provenanceScore": 88, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install openai azure-identity # or: npm i openai @azure/identity", "http": "curl \"https://$AZURE_OPENAI_RESOURCE.openai.azure.com/openai/v1/responses\" \\\n -H \"api-key: $AZURE_OPENAI_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"\u003cyour-deployment-name\u003e\",\"input\":\"hello\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/azure-openai" }, "sameCompany": [ "azure-foundry-fine-tuning", "azure-ai-content-safety", "azure-speech-to-text", "azure-text-to-speech", "microsoft-agent-framework", "microsoft-execution-containers", "microsoft-entra-agent-id", "azure-key-vault", "bing-grounding", "azure-document-intelligence", "azure-devops-mcp", "microsoft-learn-mcp", "tokeneconomizer", "playwright-mcp", "azure-mcp", "azure-maps", "azure-translator", "microsoft-graph-calendar", "azure-blob-storage", "onedrive-sharepoint", "microsoft-teams", "dynamics-365-sales", "copilot-studio-mcp", "power-automate", "foundry-local", "microsoft-decision-1", "microsoft-advertising-api", "microsoft-excel-graph", "outlook-mail-graph", "microsoft-graph-people", "mage-vl-cowork" ], "area": "models", "unitPrices": [ { "item": "GPT-6.1 Sol input, Global Standard", "unit": "1m-tokens", "usd": 2, "note": "short context, Retail Prices API meter effective 2026-10-01" }, { "item": "GPT-6.1 Sol output, Global Standard", "unit": "1m-tokens", "usd": 10, "note": "short context" }, { "item": "GPT-6.1 Terra input, Global Standard", "unit": "1m-tokens", "usd": 1, "note": "short context" }, { "item": "GPT-6.1 Terra output, Global Standard", "unit": "1m-tokens", "usd": 5, "note": "short context" }, { "item": "GPT-6 Astra input, Global Standard", "unit": "1m-tokens", "usd": 10, "note": "short context" }, { "item": "GPT-6 Astra output, Global Standard", "unit": "1m-tokens", "usd": 50, "note": "short context" } ], "provenance": { "legalEntity": "Microsoft Corporation", "domain": "microsoft.com", "domainRegistered": "1991-05-02", "domainNote": "Endpoints are on openai.azure.com and cognitiveservices.azure.com. microsoft.com publishes a security.txt, but it passed its Expires date on 2026-09-23 and was still expired on 2026-11-06.", "endpointOnVendorDomain": true, "terms": "https://www.microsoft.com/licensing/terms/product/ForOnlineServices/all", "privacy": "https://privacy.microsoft.com/en-us/privacystatement", "statusPage": "https://azure.status.microsoft/en-us/status", "changelog": "https://learn.microsoft.com/en-us/azure/foundry/whats-new-foundry", "securityTxt": "expired", "checked": "2026-11-06", "score": 88 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/azure-openai.json", "live": { "slug": "azure-openai", "probe": { "target": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "method": "get", "lastAt": "2026-11-07T18:20:12.145420458Z", "lastOk": false, "lastStatus": 0, "lastMs": 0, "lastNote": "DNS lookup failed", "authRequired": false, "uptime24h": 0, "uptime30d": 0, "p50ms24h": 0, "p95ms24h": 0, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 0 }, { "date": "2026-11-07", "probes": 187, "ok": 0 } ], "outages": [ { "start": "2026-11-06T22:45:05.888142257Z", "end": "0001-01-01T00:00:00Z", "note": "DNS lookup failed" } ] }, "versions": [ { "registry": "npm", "name": "@azure/openai", "version": "2.0.0", "seenAt": "2026-11-06T23:09:28.988578937Z" }, { "registry": "npm", "name": "openai", "version": "7.53.0", "seenAt": "2026-11-06T23:09:28.954764315Z" }, { "registry": "pypi", "name": "openai", "version": "3.46.0", "released": "2026-11-05", "seenAt": "2026-11-06T23:09:28.844701934Z" } ], "githubStars": 3113, "npmWeekly": 56543040, "pypiWeekly": 91156146, "securityTxt": { "url": "https://microsoft.com/.well-known/security.txt", "state": "valid", "expires": "2027-10-27T16:00:00.000Z", "checkedAt": "2026-11-07T16:02:01.196666056Z" }, "pages": [ { "url": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:13:01.613678733Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "51438ff38076" } ], "updatedAt": "2026-11-07T18:20:12.145420458Z" } }, "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Cerebras Inference's 68.6 (B), and leads in 5 of 7 scored categories. Cerebras Inference leads on schema \u0026 documentation.", "b": { "slug": "cerebras-inference", "name": "Cerebras Inference", "vendor": "Cerebras Systems Inc.", "vendorUrl": "https://www.cerebras.ai/inference", "kind": "http-api", "category": "inference", "summary": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API. It supports streaming, structured outputs, tool calling and prompt caching, with shared and dedicated inference options.", "url": "https://www.anchorterminal.com/tools/cerebras-inference", "markdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json", "dns": "cerebras-inference.grade.anchorterminal.com", "repo": "https://github.com/Cerebras/cerebras-cloud-sdk-python", "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.cerebras.ai/v1", "packages": [ { "registry": "pypi", "name": "cerebras-cloud-sdk" }, { "registry": "npm", "name": "@cerebras/cerebras_cloud_sdk" } ], "auth": "api-key", "authNotes": "Bearer API keys from the Cloud Console. Paid accounts scope keys to projects; trial accounts do not have projects. Keys do not expire and can be rotated by creating a replacement and deleting the old key.", "pricing": "paid", "pricingNotes": "Pay per token. GPT OSS 120B is $0.35 per million input tokens and $0.75 per million output tokens. New accounts get $5 for 30 days only after adding a verified payment method. Dedicated capacity is priced by agreement.", "priceSummary": "Paid", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 170, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://inference-docs.cerebras.ai", "llmsTxt": "https://inference-docs.cerebras.ai/llms.txt", "openapi": "https://inference-docs.cerebras.ai/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "http-api", "inference", "api-key", "openapi", "llms-txt", "paid" ], "lastRelease": "2026-10-28", "graded": true, "anchor": { "graded": true, "score": 68.6, "grade": "B", "agentReady": false, "rank": 277, "ranked": true, "rankOf": 1486, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 60 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.", "bestFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "strengths": [ "Public OpenAPI 3.1, Markdown docs, and official Python and TypeScript SDKs", "Tool calling, structured outputs, streaming and prompt caching on supported models", "Documented project controls, usage logs and numeric request and token limits" ], "weaknesses": [ "Trial access requires a verified payment method and ends after $5 or 30 days", "The GPT OSS model page and central rate-limit page disagree on trial request limits", "Cloud terms returned an empty page to the reader; no public shared-inference SLA was established" ], "agentNotes": [ "Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.", "Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.", "Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.", "Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 68.6 } ], "editorialScores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 45 }, "provenanceScore": 75, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-10-27", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl 'https://api.cerebras.ai/v1/chat/completions' -H \"Authorization: Bearer $CEREBRAS_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/cerebras-inference" }, "area": "models", "unitPrices": [ { "item": "GPT OSS 120B input", "unit": "1m-tokens", "usd": 0.35, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" }, { "item": "GPT OSS 120B output", "unit": "1m-tokens", "usd": 0.75, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" } ], "provenance": { "legalEntity": "Cerebras Systems Inc.", "domain": "cerebras.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://cloud.cerebras.ai/terms", "privacy": "https://www.cerebras.ai/privacy-policy", "statusPage": "https://status.cerebras.ai", "changelog": "https://inference-docs.cerebras.ai/support/change-log", "securityTxt": "none", "checked": "2026-11-01", "notes": [ "Legal identity comes from the vendor policy pages. Domain registration was not checked.", "The SDK repository is not the source for the hosted inference service.", "Cloud terms at cloud.cerebras.ai/terms returned no readable document on 19 October and weren't re-read on 1 November; privacy identifies Cerebras Systems Inc.", "The well-known security.txt at www.cerebras.ai returned 404 again on 1 November 2026. The trust centre lists SOC 2 Type II." ], "score": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cerebras-inference.json", "live": { "slug": "cerebras-inference", "probe": { "target": "https://api.cerebras.ai/v1", "method": "get", "lastAt": "2026-11-07T18:20:16.272240927Z", "lastOk": true, "lastStatus": 404, "lastMs": 148, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 133, "p95ms24h": 213, "samples24h": 239, "samples30d": 4786, "days": [ { "date": "2026-10-19", "probes": 173, "ok": 173 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 248, "ok": 248 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "vendorStatus": { "page": "https://status.cerebras.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T18:20:38.492291797Z" }, "versions": [ { "registry": "npm", "name": "@cerebras/cerebras_cloud_sdk", "version": "1.91.0", "seenAt": "2026-11-06T23:13:49.446971954Z" }, { "registry": "pypi", "name": "cerebras-cloud-sdk", "version": "1.91.0", "released": "2026-07-16", "seenAt": "2026-11-06T23:13:49.262026332Z" } ], "githubStars": 173, "npmWeekly": 180448, "pypiWeekly": 249281, "securityTxt": { "url": "https://cerebras.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:42.51446288Z" }, "llmsTxt": { "url": "https://inference-docs.cerebras.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:47.130010713Z" }, "domain": { "domain": "cerebras.ai", "registered": "2017-12-15", "source": "https://rdap.identitydigital.services/rdap/domain/cerebras.ai", "checkedAt": "2026-11-01T14:11:27.609133686Z" }, "pages": [ { "url": "https://inference-docs.cerebras.ai/support/change-log", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:11:30.48401691Z", "changedAt": "2026-10-29T05:08:49.839928383Z", "fingerprint": "a8abcec170f3" }, { "url": "https://www.cerebras.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:26:28.792856066Z", "changedAt": "2026-11-06T13:47:29.432265889Z", "fingerprint": "218d0061c477" }, { "url": "https://cloud.cerebras.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:01:12.525816134Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "32931218130a" } ], "github": { "repo": "cerebras/cerebras-cloud-sdk-python", "checkedAt": "2026-11-02T08:24:38.010800971Z", "stars": 174, "archived": false, "issuesEnabled": true, "pushedAt": "2026-07-16T17:08:17Z", "openIssues": 1, "openPRs": 0, "issuesOpened90d": 2, "issuesClosed90d": 1, "prsMerged90d": 0, "replies": { "sampled": 12, "unanswered": 0, "medianDays": 35.4 } }, "updatedAt": "2026-11-07T18:20:16.272240927Z" } }, "edges": [ { "by": 25, "category": "security", "leads": "azure-openai", "name": "Security \u0026 auth", "reasons": { "a": "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).", "b": "Revocable Bearer keys with rotation instructions (20). Paid-project boundaries, but no inference-only key permission found (10 of 20). GPT OSS documentation warns about undeclared tool calls and tells callers to validate them (10 of 15). Request and audit logs in the console (15). Trust centre lists SOC 2 Type II, with reports requiring access (15 of 20)." }, "scores": { "a": 95, "b": 70 } }, { "by": 23, "category": "transparency", "leads": "azure-openai", "name": "Transparency \u0026 trust", "reasons": { "a": "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).", "b": "SDK is Apache-2.0, but the hosted cloud terms were not readable in this session (5 of 30). Privacy policy states no inference input/output retention but gives no fixed operational-log retention period (20 of 30). Dated deprecations and API-version migration guidance without a general minimum notice commitment found (10 of 20). Trust centre lists subprocessors and infrastructure controls, but full data-location details were not established (10 of 20)." }, "scores": { "a": 83, "b": 60 } }, { "by": 21, "category": "maintenance", "leads": "azure-openai", "name": "Maintenance \u0026 community", "reasons": { "a": "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\u0026A 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).", "b": "Dated changelog entry on 28 October 2026, adding five models to the Dedicated catalogue and documenting image inputs in tool messages and new reasoning controls (30). Seven dated changelog entries in the 90 days from 3 August, on 28 and 31 August, two on 3 September, 22 September, 9 October and 28 October (20). Support responsiveness not established (0). Official Python and TypeScript SDKs, both last released as 1.91.0 on 8 July 2026 (15). Runtime dependency health and CI were not audited (0)." }, "scores": { "a": 86, "b": 65 } }, { "by": 13, "category": "ergonomics", "leads": "azure-openai", "name": "Agent ergonomics", "reasons": { "a": "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.", "b": "Model API with bounded output and compact request shape (25). Output token controls, streaming and structured outputs (20). Documented error classes and fixes (20). Bounded transient retries but no request-deduplication guarantee established (5 of 20). Defaults and official Python and TypeScript SDKs (15)." }, "scores": { "a": 98, "b": 85 } }, { "by": 10, "category": "reliability", "leads": "azure-openai", "name": "Reliability", "reasons": { "a": "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).", "b": "Graded as listed, on the hosted API lines. Public component status history at status.cerebras.ai, with components for GPT-OSS-120B, Qwen-3.8-27b and the Developer Console (20). The history feed, read on 1 November 2026, runs back to November 2025, so the whole 90 days from 3 August were read. On 25 September 2026 Cerebras posted that parts of the service might be unavailable from 10:54 UTC, services were back at 13:41 UTC and the incident was resolved at 17:14 UTC, marked major and affecting both public model components. That is about 2 hours 47 minutes with the whole shared catalogue affected, one major. A 15-minute partial degradation of Gemma 4 31B on 27 August is minor, and the 30 August firewall maintenance was announced on 25 August (10). Numeric rate-limit tables, although the trial request limit is 5 a minute on the rate-limits page and 30 a minute on the GPT OSS page, re-read on 1 November (15). SDK error classes and bounded retries with backoff (15). No public shared-inference SLA established (0). Shared inference is generally available (10)." }, "scores": { "a": 80, "b": 70 } }, { "by": 6, "category": "schema", "leads": "cerebras-inference", "name": "Schema \u0026 documentation", "reasons": { "a": "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).", "b": "Public OpenAPI 3.1 (25), llms.txt and Markdown pages (10), documented capability and compatibility limits (16 of 20), typed inputs and constrained parameters (13 of 15), examples and error guidance (14 of 15), and API versions plus dated changelog (15)." }, "scores": { "a": 87, "b": 93 } } ], "facts": [ { "a": "Model API", "b": "HTTP API", "name": "Kind" }, { "a": "Microsoft", "b": "Cerebras Systems Inc.", "name": "Vendor" }, { "a": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "b": "https://api.cerebras.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Paid", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the Microsoft Product Terms. The v1 OpenAPI spec is MIT, and the OpenAI SDKs the docs use are Apache-2.0", "b": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-26", "b": "2026-10-28", "name": "Last release" }, { "a": "no date given", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "2026-09-01", "b": "2024-08-27", "name": "Privacy policy last updated" }, { "a": "yes", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "yes", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "yes", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "454k npm/wk", "b": "170 stars", "name": "Popularity" }, { "a": "none", "b": "3.3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Cerebras Inference's 68.6 (B), and leads in 5 of 7 scored categories. Cerebras Inference leads on schema \u0026 documentation.", "question": "Which is better for AI agents, Azure OpenAI in Foundry Models or Cerebras Inference?" }, { "answer": "Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Cerebras Inference needs an API key.", "question": "Do Azure OpenAI in Foundry Models and Cerebras Inference need an API key?" }, { "answer": "Yes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and Cerebras Inference at https://api.cerebras.ai/v1.", "question": "Can an agent call Azure OpenAI in Foundry Models and Cerebras Inference without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 80 against 70", "Agent ergonomics, 98 against 85", "Security \u0026 auth, 95 against 70", "Maintenance \u0026 community, 86 against 65", "Transparency \u0026 trust, 83 against 60" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "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.", "slug": "azure-openai", "watchFor": "Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026" }, { "aheadOn": [ "Schema \u0026 documentation, 93 against 87" ], "also": null, "goodFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "slug": "cerebras-inference", "watchFor": "Trial access requires a verified payment method and ends after $5 or 30 days" } ], "history": { "azure-openai": null, "cerebras-inference": [ { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.2, "from": 68.4, "fromGrade": "B", "to": 68.6, "toGrade": "B" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.json", "title": "Amazon Bedrock vs Azure OpenAI in Foundry Models", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.json", "title": "Amazon Bedrock vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference" }, { "json": 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"https://www.anchorterminal.com/compare/cerebras-inference-vs-minimax-api.json", "title": "Cerebras Inference vs MiniMax API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-mistral-api.json", "title": "Cerebras Inference vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open.json", "title": "Cerebras Inference vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-nemotron-3-5-super-vl.json", "title": "Cerebras Inference vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-novita-ai.json", "title": "Cerebras Inference vs Novita AI", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api.json", "title": "Cerebras Inference vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openrouter.json", "title": "Cerebras Inference vs OpenRouter", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-prism-inference.json", "title": "Cerebras Inference vs Prism Inference", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-ramp-router.json", "title": "Cerebras Inference vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam.json", "title": "Cerebras Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-routerplus.json", "title": "Cerebras Inference vs RouterPlus", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-sambanova.json", "title": "Cerebras Inference vs SambaCloud", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow.json", "title": "Cerebras Inference vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-simplismart.json", "title": "Cerebras Inference vs Simplismart", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-stepfun-api.json", "title": "Cerebras Inference vs StepFun API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-swe-2-flash.json", "title": "Cerebras Inference vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-tencent-tokenhub.json", "title": "Cerebras Inference vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-together-inference.json", "title": "Cerebras Inference vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vercel-ai-gateway.json", "title": "Cerebras Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.json", "title": "Cerebras Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-xai-api.json", "title": "Cerebras Inference vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-xai-api" } ], "panel": null, "scores": [ { "azure-openai": 80, "by": 10, "cerebras-inference": 70, "edge": "azure-openai", "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-openai": 87, "by": 6, "cerebras-inference": 93, "edge": "cerebras-inference", "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "azure-openai": 98, "by": 13, "cerebras-inference": 85, "edge": "azure-openai", "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "azure-openai": 95, "by": 25, "cerebras-inference": 70, "edge": "azure-openai", "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "azure-openai": 20, "by": 0, "cerebras-inference": 20, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-openai": 86, "by": 21, "cerebras-inference": 65, "edge": "azure-openai", "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "azure-openai": 83, "by": 23, "cerebras-inference": 60, "edge": "azure-openai", "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Cerebras Inference's 68.6 (B), and leads in 5 of 7 scored categories. Cerebras Inference leads on schema \u0026 documentation. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "azure-openai": "An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.", "cerebras-inference": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference", "json": "https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.min.md" }, "markdown": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Cerebras Inference's 68.6 (B), and leads in 5 of 7 scored categories. Cerebras Inference leads on schema \u0026 documentation. Both do llm inference.\n\n- Azure OpenAI in Foundry Models: grade A, 80/100, rank #14 of 1486. Markdown https://www.anchorterminal.com/tools/azure-openai.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-openai.json\n- Cerebras Inference: grade B, 68.6/100, rank #277 of 1486. Markdown https://www.anchorterminal.com/tools/cerebras-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Azure OpenAI in Foundry Models (A)\n\nGood 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.\n\nAhead on:\n- Reliability, 80 against 70\n- Agent ergonomics, 98 against 85\n- Security \u0026 auth, 95 against 70\n- Maintenance \u0026 community, 86 against 65\n- Transparency \u0026 trust, 83 against 60\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026\n\n### Cerebras Inference (B)\n\nGood for: Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.\n\nAhead on:\n- Schema \u0026 documentation, 93 against 87\n\nWatch for: Trial access requires a verified payment method and ends after $5 or 30 days\n\n\n## Why the edge\n\n### Security \u0026 auth: Azure OpenAI in Foundry Models +25\n\n- 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).\n- Cerebras Inference (70): Revocable Bearer keys with rotation instructions (20). Paid-project boundaries, but no inference-only key permission found (10 of 20). GPT OSS documentation warns about undeclared tool calls and tells callers to validate them (10 of 15). Request and audit logs in the console (15). Trust centre lists SOC 2 Type II, with reports requiring access (15 of 20).\n\n### Transparency \u0026 trust: Azure OpenAI in Foundry Models +23\n\n- 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).\n- Cerebras Inference (60): SDK is Apache-2.0, but the hosted cloud terms were not readable in this session (5 of 30). Privacy policy states no inference input/output retention but gives no fixed operational-log retention period (20 of 30). Dated deprecations and API-version migration guidance without a general minimum notice commitment found (10 of 20). Trust centre lists subprocessors and infrastructure controls, but full data-location details were not established (10 of 20).\n\n### Maintenance \u0026 community: Azure OpenAI in Foundry Models +21\n\n- 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\u0026A 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).\n- Cerebras Inference (65): Dated changelog entry on 28 October 2026, adding five models to the Dedicated catalogue and documenting image inputs in tool messages and new reasoning controls (30). Seven dated changelog entries in the 90 days from 3 August, on 28 and 31 August, two on 3 September, 22 September, 9 October and 28 October (20). Support responsiveness not established (0). Official Python and TypeScript SDKs, both last released as 1.91.0 on 8 July 2026 (15). Runtime dependency health and CI were not audited (0).\n\n### Agent ergonomics: Azure OpenAI in Foundry Models +13\n\n- 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.\n- Cerebras Inference (85): Model API with bounded output and compact request shape (25). Output token controls, streaming and structured outputs (20). Documented error classes and fixes (20). Bounded transient retries but no request-deduplication guarantee established (5 of 20). Defaults and official Python and TypeScript SDKs (15).\n\n### Reliability: Azure OpenAI in Foundry Models +10\n\n- 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).\n- Cerebras Inference (70): Graded as listed, on the hosted API lines. Public component status history at status.cerebras.ai, with components for GPT-OSS-120B, Qwen-3.8-27b and the Developer Console (20). The history feed, read on 1 November 2026, runs back to November 2025, so the whole 90 days from 3 August were read. On 25 September 2026 Cerebras posted that parts of the service might be unavailable from 10:54 UTC, services were back at 13:41 UTC and the incident was resolved at 17:14 UTC, marked major and affecting both public model components. That is about 2 hours 47 minutes with the whole shared catalogue affected, one major. A 15-minute partial degradation of Gemma 4 31B on 27 August is minor, and the 30 August firewall maintenance was announced on 25 August (10). Numeric rate-limit tables, although the trial request limit is 5 a minute on the rate-limits page and 30 a minute on the GPT OSS page, re-read on 1 November (15). SDK error classes and bounded retries with backoff (15). No public shared-inference SLA established (0). Shared inference is generally available (10).\n\n### Schema \u0026 documentation: Cerebras Inference +6\n\n- 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).\n- Cerebras Inference (93): Public OpenAPI 3.1 (25), llms.txt and Markdown pages (10), documented capability and compatibility limits (16 of 20), typed inputs and constrained parameters (13 of 15), examples and error guidance (14 of 15), and API versions plus dated changelog (15).\n\n## Score by category\n\n| Category | Weight | Azure OpenAI in Foundry Models | Cerebras Inference | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 70 | Azure OpenAI in Foundry Models +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 87 | 93 | Cerebras Inference +6 |\n| Agent ergonomics | 13% (16.2 this run) | 98 | 85 | Azure OpenAI in Foundry Models +13 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 70 | Azure OpenAI in Foundry Models +25 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 86 | 65 | Azure OpenAI in Foundry Models +21 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 83 | 60 | Azure OpenAI in Foundry Models +23 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **80 · A** | **68.6 · B** | |\n\n## Facts side by side\n\n| Fact | Azure OpenAI in Foundry Models | Cerebras Inference |\n| --- | --- | --- |\n| Kind | Model API | HTTP API |\n| Vendor | Microsoft | Cerebras Systems Inc. |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | `https://api.cerebras.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Paid |\n| x402 | no | no |\n| 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 | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-26 | 2026-10-28 |\n| Terms last updated | no date given | couldn't be read |\n| Privacy policy last updated | 2026-09-01 | 2024-08-27 |\n| Customer content may train models | yes | couldn't be read |\n| Terms restrict automated access | yes | couldn't be read |\n| Terms restrict benchmarking | yes | couldn't be read |\n| Terms or service can change without notice | not found in the text | couldn't be read |\n| Arbitration or class-action waiver | not found in the text | couldn't be read |\n| Popularity | 454k npm/wk | 170 stars |\n| Agent reviews | none | 3.3/5 (4) |\n\n## How the scores have moved\n\n### Azure OpenAI in Foundry Models\n\nNo score change since it was listed.\n\n### Cerebras Inference\n\n- +0.2 on 27 October 2026: checklist\n\n## Verdicts\n\n**Azure OpenAI in Foundry Models.** An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.\n\n**Cerebras Inference.** An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.\n\n## Before you call either\n\n### Azure OpenAI in Foundry Models\n\n1. Point the OpenAI SDK at https://\u003cresource\u003e.openai.azure.com/openai/v1/ and pass the deployment name as `model`, not the model id\n2. Prefer Entra ID with the Cognitive Services OpenAI User role over the resource key, which opens the whole data plane\n3. On 429 wait for `retry-after-ms`, then back off with jitter. The OpenAI SDK retries twice by default\n4. Set `store: false` on Responses calls you don't need kept. Stored responses persist 30 days by default\n5. Keep remote MCP approvals on for servers you don't control. They're required by default\n\n### Cerebras Inference\n\n1. Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.\n2. Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.\n3. Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.\n4. Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated.\n\n## Questions\n\n### Which is better for AI agents, Azure OpenAI in Foundry Models or Cerebras Inference?\n\nAzure OpenAI in Foundry Models scores 80 (A) on agent readiness against Cerebras Inference's 68.6 (B), and leads in 5 of 7 scored categories. Cerebras Inference leads on schema \u0026 documentation.\n\n### Do Azure OpenAI in Foundry Models and Cerebras Inference need an API key?\n\nAzure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Cerebras Inference needs an API key.\n\n### Can an agent call Azure OpenAI in Foundry Models and Cerebras Inference without installing anything?\n\nYes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and Cerebras Inference at https://api.cerebras.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-openai\", \"b\": \"cerebras-inference\"}`. From a terminal: `anchor compare azure-openai cerebras-inference`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-openai.json and https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json\n\n## Other comparisons with Azure OpenAI in Foundry Models or Cerebras Inference\n\n- [Amazon Bedrock vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.md)\n- [Amazon Bedrock vs Cerebras Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.md)\n- [Claude API vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai.md)\n- [Claude API vs Cerebras Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs Cerebras 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OpenAI in Foundry Models vs Glimpse](https://www.anchorterminal.com/compare/azure-openai-vs-elorian-glimpse.md)\n- [Azure OpenAI in Foundry Models vs Fireworks AI Inference](https://www.anchorterminal.com/compare/azure-openai-vs-fireworks-inference.md)\n- [Azure OpenAI in Foundry Models vs Gemini Developer API](https://www.anchorterminal.com/compare/azure-openai-vs-gemini-api.md)\n- [Azure OpenAI in Foundry Models vs GroqCloud](https://www.anchorterminal.com/compare/azure-openai-vs-groq.md)\n- [Azure OpenAI in Foundry Models vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.md)\n- [Azure OpenAI in Foundry Models vs Inkling 2 Small](https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small.md)\n- [Azure OpenAI in Foundry Models vs Jais 3](https://www.anchorterminal.com/compare/azure-openai-vs-jais-3.md)\n- [Azure OpenAI in Foundry Models vs Meta Model 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Flash](https://www.anchorterminal.com/compare/azure-openai-vs-swe-2-flash.md)\n- [Azure OpenAI in Foundry Models vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/azure-openai-vs-tencent-tokenhub.md)\n- [Azure OpenAI in Foundry Models vs Together AI Inference](https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.md)\n- [Azure OpenAI in Foundry Models vs Vercel AI Gateway](https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway.md)\n- [Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.md)\n- [Azure OpenAI in Foundry Models vs xAI API (Grok)](https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.md)\n- [BlockRun.AI vs Cerebras Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-cerebras-inference.md)\n- [Cerebras Inference vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/cerebras-inference-vs-cloudflare-ai-gateway.md)\n- [Cerebras Inference vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-cloudflare-workers-ai.md)\n- [Cerebras Inference vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/cerebras-inference-vs-cohere-chat.md)\n- [Cerebras Inference vs DeepInfra](https://www.anchorterminal.com/compare/cerebras-inference-vs-deepinfra.md)\n- [Cerebras Inference vs DeepSeek API](https://www.anchorterminal.com/compare/cerebras-inference-vs-deepseek-api.md)\n- [Cerebras Inference vs Eden AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai.md)\n- [Cerebras Inference vs Glimpse](https://www.anchorterminal.com/compare/cerebras-inference-vs-elorian-glimpse.md)\n- [Cerebras Inference vs Fireworks AI Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-fireworks-inference.md)\n- [Cerebras Inference vs Gemini Developer 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Open](https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open.md)\n- [Cerebras Inference vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/cerebras-inference-vs-nemotron-3-5-super-vl.md)\n- [Cerebras Inference vs Novita AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-novita-ai.md)\n- [Cerebras Inference vs OpenAI API](https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api.md)\n- [Cerebras Inference vs OpenRouter](https://www.anchorterminal.com/compare/cerebras-inference-vs-openrouter.md)\n- [Cerebras Inference vs Prism Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-prism-inference.md)\n- [Cerebras Inference vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/cerebras-inference-vs-ramp-router.md)\n- [Cerebras Inference vs Beam 1.0](https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam.md)\n- [Cerebras Inference vs RouterPlus](https://www.anchorterminal.com/compare/cerebras-inference-vs-routerplus.md)\n- [Cerebras Inference vs SambaCloud](https://www.anchorterminal.com/compare/cerebras-inference-vs-sambanova.md)\n- [Cerebras Inference vs SiliconFlow](https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow.md)\n- [Cerebras Inference vs Simplismart](https://www.anchorterminal.com/compare/cerebras-inference-vs-simplismart.md)\n- [Cerebras Inference vs StepFun API](https://www.anchorterminal.com/compare/cerebras-inference-vs-stepfun-api.md)\n- [Cerebras Inference vs SWE-2 Flash](https://www.anchorterminal.com/compare/cerebras-inference-vs-swe-2-flash.md)\n- [Cerebras Inference vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/cerebras-inference-vs-tencent-tokenhub.md)\n- [Cerebras Inference vs Together AI Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-together-inference.md)\n- [Cerebras Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/cerebras-inference-vs-vercel-ai-gateway.md)\n- [Cerebras Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/cerebras-inference-vs-vertex-ai.md)\n- [Cerebras Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/cerebras-inference-vs-xai-api.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Azure OpenAI in Foundry Models vs Cerebras Inference", "url": "" } ], "description": "Azure OpenAI in Foundry Models scores 80 (A) to Cerebras Inference's 68.6 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Azure OpenAI in Foundry Models A 80", "Cerebras Inference B 68.6", "scores" ], "h1": "Azure OpenAI in Foundry Models vs Cerebras Inference", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/azure-openai-vs-cerebras-inference", "published": "2026-10-01", "section": "tools", "title": "Azure OpenAI in Foundry Models vs Cerebras Inference (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference" }, "tokens": { "markdown": 7050, "slim": 3380 }, "version": 1 }