{ "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": 1510, "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": "2026-11-07T19:21:54.262001342Z", "lastOk": false, "lastStatus": 0, "lastMs": 0, "lastNote": "DNS lookup failed", "authRequired": false, "uptime24h": 0, "uptime30d": 0, "p50ms24h": 0, "p95ms24h": 0, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 0 }, { "date": "2026-11-07", "probes": 197, "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": "2026-11-07T19:21:54.262001342Z" } }, "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against xAI API (Grok)'s 71.7 (BB), and leads in 4 of 7 scored categories.", "b": { "slug": "xai-api", "name": "xAI API (Grok)", "vendor": "SpaceXSI (xAI)", "vendorUrl": "https://x.ai", "kind": "model", "category": "inference", "summary": "xAI's API for its Grok models (the docs now name the company SpaceXSI), with text, image, video and voice endpoints, server-side search and remote MCP tools, through an OpenAI-compatible REST API or gRPC.", "url": "https://www.anchorterminal.com/tools/xai-api", "markdownUrl": "https://www.anchorterminal.com/tools/xai-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/xai-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/xai-api.json", "dns": "xai-api.grade.anchorterminal.com", "repo": "https://github.com/xai-org/xai-sdk-python", "license": "Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://api.x.ai/v1", "packages": [ { "registry": "pypi", "name": "xai-sdk" } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a team API key from console.x.ai. Keys can be limited to endpoints and models by ACL, capped by QPM and TPM, given an expiry, and rotated or disabled through the Management API. mTLS is documented as an option, and GitHub secret scanning disables leaked keys.", "pricing": "usage", "pricingNotes": "Prepaid credits, then the default payment method at month end. Grok 4.7 costs $2 input, $0.50 cached input and $6 output per 1M tokens below 200K prompt tokens, and $4/$1/$12 above, applied to the whole request. Batch is 20% off on grok-4.7, 4.6, 4.5, 4.3 and the grok-4.20 models. Priority processing 2x, the US regional endpoint 1.1x. Web search, code execution and attachment search $5 per 1,000 calls, collections search $2.50, X search $5 per 1,000 posts. $0.05 fee for a request blocked before generation for a usage-policy violation (https://docs.x.ai/developers/pricing, checked 2026-11-06).", "priceSummary": "from $1.25 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, llms.txt or the OpenAPI spec. Access needs a console account loaded with prepaid credits (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 597, "npmWeekly": null, "pypiWeekly": 912149, "asOf": "2026-11-06" }, "docsUrl": "https://docs.x.ai", "rateLimitsUrl": "https://docs.x.ai/developers/rate-limits", "llmsTxt": "https://docs.x.ai/llms.txt", "openapi": "https://docs.x.ai/openapi.json", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "prepaid", "openapi", "llms-txt", "openai-compatible", "closed-source", "python", "batch", "status-page", "bug-bounty", "soc2" ], "lastRelease": "2026-11-02", "graded": true, "anchor": { "graded": true, "score": 71.7, "grade": "BB", "agentReady": true, "rank": 152, "ranked": true, "rankOf": 1510, "categoryRank": 8, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 90, "maintenance": 77, "payments": 20, "reliability": 55, "schema": 88, "security": 97, "transparency": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python.", "bestFor": "Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.", "strengths": [ "Grok 4.7 at $2/$6 per million tokens below 200K prompt tokens, with a 500K context and 20% off through the Batch API", "API keys restricted by endpoint and model ACLs, with QPM and TPM caps, expiry and a rotate endpoint", "Self-serve team-wide zero data retention, confirmed on every response by an `x-zero-data-retention` header", "OpenAPI 3.1 spec, llms.txt and a Markdown twin of every docs page", "security.txt valid to 2027-06-29 and a HackerOne bug bounty" ], "weaknesses": [ "API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August", "No SLA, no free tier for the text API, and no Retry-After header documented for 429s", "No stated minimum notice for retirements, and retired slugs are served by a different model at its price", "Remote MCP doesn't support `require_approval`, so server-side tool calls run without an approval step", "The terms, privacy policy and DPA at x.ai/legal answered a Cloudflare block on 6 October and 6 November 2026, so they weren't read" ], "agentNotes": [ "Build on the Responses API at https://api.x.ai/v1. Chat Completions is labelled deprecated and the Anthropic-compatible endpoint fully deprecated", "Pin a dated model slug. A retired slug keeps answering from a replacement model, billed at the replacement's price", "Back off exponentially on 429. The per-second cap is the per-minute budget divided by 48, with a minimum of 2", "Set `allowed_tools` on remote MCP servers. There's no approval step, and every exposed tool enters the context", "Use https://us.api.x.ai/v1 when processing must stay in the US. It costs 1.1x and serves only grok-4.7 and grok-4.6" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 71.7 } ], "editorialScores": { "ergonomics": 90, "maintenance": 77, "payments": 20, "reliability": 55, "schema": 88, "security": 97, "transparency": 52 }, "provenanceScore": 73, "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 xai-sdk # or: pip install openai, with base_url https://api.x.ai/v1", "http": "curl https://api.x.ai/v1/responses \\\n -H \"Authorization: Bearer $XAI_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"grok-4.7\",\"input\":\"What is the meaning of life?\"}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/xai-api" }, "area": "models", "unitPrices": [ { "item": "Web search tool", "unit": "1k-requests", "usd": 5 }, { "item": "Code execution tool", "unit": "1k-requests", "usd": 5 }, { "item": "Collections search tool", "unit": "1k-requests", "usd": 2.5 } ], "provenance": { "legalEntity": "", "domain": "x.ai", "domainRegistered": "2017-12-16", "domainNote": "x.ai was registered in 2017, before the company, and transferred on 2026-06-02 per RDAP. Every x.ai page except robots.txt and security.txt answered a Cloudflare block page (403) on 2026-11-06, as the legal pages did on 2026-10-06, so the contracting entity wasn't confirmed. The docs now use the name SpaceXSI and the status page SpaceXAI.", "endpointOnVendorDomain": true, "terms": "https://x.ai/legal/terms-of-service-enterprise", "privacy": "https://x.ai/legal/privacy-policy", "statusPage": "https://status.x.ai", "changelog": "https://docs.x.ai/developers/release-notes", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "x.ai/robots.txt allows all but /tools/, with Content-Signal ai-train=yes, search=yes, ai-input=yes. docs.x.ai allows all with ai-input=yes. The x.ai pages that robots.txt allows answered a Cloudflare 'Attention Required' page, which we did not try to get past.", "security.txt at x.ai/.well-known/security.txt is valid to 2027-06-29, with vulnerabilities@x.ai and abuse@x.ai." ], "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/xai-api.json", "live": { "slug": "xai-api", "probe": { "target": "https://api.x.ai/v1", "method": "get", "lastAt": "2026-11-07T19:22:45.426736159Z", "lastOk": true, "lastStatus": 404, "lastMs": 193, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 178, "p95ms24h": 276, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "vendorStatus": { "page": "https://status.x.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:49:01.143662157Z" }, "versions": [ { "registry": "github", "name": "xai-org/xai-sdk-python", "version": "v1.21.0", "released": "2026-10-23", "seenAt": "2026-11-07T00:18:15.193708838Z" }, { "registry": "pypi", "name": "xai-sdk", "version": "1.21.0", "released": "2026-10-23", "seenAt": "2026-11-07T00:18:15.09038487Z" } ], "githubStars": 598, "pypiWeekly": 912149, "securityTxt": { "url": "https://x.ai/.well-known/security.txt", "state": "valid", "expires": "2027-06-29T00:00:00.000Z", "checkedAt": "2026-11-07T16:01:43.978620532Z" }, "llmsTxt": { "url": "https://docs.x.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:34:24.762831371Z" }, "pages": [ { "url": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:08:46.034096807Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "1238569c8142" }, { "url": "https://docs.x.ai/developers/migration/may-15-retirement", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:08:48.207542223Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "813d0e188a0e" }, { "url": "https://docs.x.ai/developers/release-notes", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:08:52.143682141Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "7b37cfaf2576" }, { "url": "https://docs.x.ai/developers/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:08:50.158330981Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "a563de9617fe" }, { "url": "https://x.ai/legal/privacy-policy", "kind": "privacy", "status": 403, "checkedAt": "2026-11-07T14:38:04.991061235Z", "changedAt": "0001-01-01T00:00:00Z" }, { "url": "https://x.ai/legal/terms-of-service-enterprise", "kind": "terms", "status": 403, "checkedAt": "2026-11-07T14:38:09.200382604Z", "changedAt": "0001-01-01T00:00:00Z" } ], "updatedAt": "2026-11-07T19:22:45.426736159Z" } }, "edges": [ { "by": 25, "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": "Status page at status.x.ai with components for the global and US API endpoints, voice, the consumer apps and, since the Cursor merger, Cursor's services, with an RSS feed (20). The feed, read on 6 November, now holds 267 incidents back to 11 August, so the whole 90-day window is readable. On the API components there were high error rates on grok-4.6 and grok-4.5 from 21:57 to 23:28 UTC on 17 August (about 90 minutes) and a models outage on the global and US endpoints from 13:30 to 17:09 UTC on 3 September (about 3 hours 40 minutes), so several majors. A 26-minute datacenter outage across the API on 22 September, voice disruptions of 12 and 28 minutes on 10 September and 6 October, a 63-minute voice and Imagine degradation on 30 October and a 37-second model degradation on 24 October add to the record (0). Rate limits published per model and tier, grok-4.7 at Tier 0 is 150 requests a second and 50M TPM, with the per-second cap derived as RPM divided by 48 (15). The rate-limits page shows exponential backoff on 429, but no Retry-After header or overload guidance was found (10 of 15). No SLA found in the docs or llms.txt (0). The Responses API has been GA since September 2025 and grok-4.7 carries no preview label (10)." }, "scores": { "a": 80, "b": 55 } }, { "by": 20, "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": "Closed service under xAI's enterprise terms, with the Python SDK under Apache-2.0 (15). The docs agree with each other on no training, 30-day abuse retention, 30-day storage of stateful responses and the ZDR route, but the privacy policy, enterprise terms and DPA at x.ai/legal answered a Cloudflare block page on 6 October and again on 6 November, so they couldn't be compared (15 of 30). Dated migration guides and redirect tables for each retirement, but no written deprecation policy, and Chat Completions, Anthropic compatibility and grok-voice-2.0 are labelled deprecated with no date (12 of 20). The US regional endpoint states what stays in the US, the global endpoint guarantees no region, and no subprocessor list was readable (10 of 20)." }, "scores": { "a": 83, "b": 63 } }, { "by": 9, "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": "Model reading. grok-imagine-image-quality and grok-imagine-image-pro retired on 2 November 2026 as announced in September, Grok Voice 3.0 and custom moderation controls in October, Grok 4.7 on 21 September (30). No minimum notice period found. Retirements come as dated migration guides, retired slugs redirect to a replacement rather than failing, billed at the replacement's price, and grok-voice-2.0 was deprecated in October with no end date (4 of 12). Shutdowns in the last 90 days with dates given in advance, `grok-voice-transcribe-1.0` on 2 October and `grok-imagine-image-quality` on 2 November (8 of 8). Release notes several times a month but dated only by month, support by email and a Discord #help channel, not tested. On xai-sdk-python a collaborator commented on 2 of the 16 most recent threads with replies, and most outside pull requests since 23 October are open without a maintainer reply (10 of 15, down from 12). The repository has CI, release and version-bump workflows (5 of 10). One current first-party SDK, `xai-sdk` 1.21.0 tagged on 23 October, Python only (10 of 15). Supported runtimes stated, Python 3.10 or later (10)." }, "scores": { "a": 86, "b": 77 } }, { "by": 8, "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 reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with parallel calls on by default and `tool_choice` of auto, required, none or a named function (20). Guaranteed structured outputs (15). Automatic prompt caching, cached input at 0.25x on grok-4.7 ($0.50 per million) and 0.16x on grok-4.3 (15). 500,000-token context on grok-4.7 and 1,000,000 on grok-4.3, 13 of 15 for the default model's 500K. The Batch API is now 20% off on grok-4.7, 4.6 and 4.5 as well as the older models, with batch requests outside the rate limits (10 of 10, up from 5 on 6 October). One first-party SDK, `xai-sdk` for Python, with the OpenAI SDKs and Vercel's AI SDK documented as alternatives (5 of 10). Status codes documented with fixes, no Retry-After header found (12 of 15)." }, "scores": { "a": 98, "b": 90 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Microsoft", "b": "SpaceXSI (xAI)", "name": "Vendor" }, { "a": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "b": "https://api.x.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": "Pay per use", "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 service under xAI's enterprise terms of service. The Python SDK is Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-26", "b": "2026-11-02", "name": "Last release" }, { "a": "no date given", "b": "2026-10-27", "name": "Terms last updated" }, { "a": "2026-09-01", "b": "2026-10-27", "name": "Privacy policy last updated" }, { "a": "yes", "b": "yes", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "454k npm/wk", "b": "597 stars, 912k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against xAI API (Grok)'s 71.7 (BB), and leads in 4 of 7 scored categories.", "question": "Which is better for AI agents, Azure OpenAI in Foundry Models or xAI API (Grok)?" }, { "answer": "Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. xAI API (Grok) needs an API key.", "question": "Do Azure OpenAI in Foundry Models and xAI API (Grok) 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 xAI API (Grok) at https://api.x.ai/v1.", "question": "Can an agent call Azure OpenAI in Foundry Models and xAI API (Grok) without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 80 against 55", "Agent ergonomics, 98 against 90", "Maintenance \u0026 community, 86 against 77", "Transparency \u0026 trust, 83 against 63" ], "also": null, "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": null, "also": null, "goodFor": "Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.", "slug": "xai-api", "watchFor": "API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August" } ], "history": null, "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-xai-api.json", "title": "Amazon Bedrock vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai.json", "title": "Claude API vs Azure OpenAI in Foundry Models", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai" }, { "json": 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"https://www.anchorterminal.com/compare/inkling-2-small-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-xai-api.json", "title": "Jais 3 vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/jais-3-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.json", "title": "Meta Model API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-xai-api.json", "title": "MiniMax API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-xai-api.json", "title": "Mistral AI API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api.json", "title": "Muse Spark Open vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-xai-api.json", "title": "Nemotron 3.5 Super VL vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api.json", "title": "Novita AI vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api.json", "title": "OpenAI API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-xai-api.json", "title": "OpenRouter vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/openrouter-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-xai-api.json", "title": "Prism Inference vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api.json", "title": "Router.com (Ramp Router) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.json", "title": "Beam 1.0 vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-xai-api.json", "title": "RouterPlus vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/routerplus-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api.json", "title": "SambaCloud vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api.json", "title": "SiliconFlow vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api.json", "title": "Simplismart vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api.json", "title": "StepFun API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-xai-api.json", "title": "SWE-2 Flash vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-xai-api.json", "title": "Tencent Cloud TokenHub vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api.json", "title": "Together AI Inference vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api.json", "title": "Vercel AI Gateway vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.json", "title": "Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api" } ], "panel": null, "scores": [ { "azure-openai": 80, "by": 25, "edge": "azure-openai", "key": "reliability", "name": "Reliability", "weight": 16, "xai-api": 55 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-openai": 87, "by": 1, "edge": "xai-api", "key": "schema", "name": "Schema \u0026 documentation", "weight": 13, "xai-api": 88 }, { "azure-openai": 98, "by": 8, "edge": "azure-openai", "key": "ergonomics", "name": "Agent ergonomics", "weight": 13, "xai-api": 90 }, { "azure-openai": 95, "by": 2, "edge": "xai-api", "key": "security", "name": "Security \u0026 auth", "weight": 14, "xai-api": 97 }, { "azure-openai": 20, "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "weight": 10, "xai-api": 20 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-openai": 86, "by": 9, "edge": "azure-openai", "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7, "xai-api": 77 }, { "azure-openai": 83, "by": 20, "edge": "azure-openai", "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7, "xai-api": 63 } ], "summary": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against xAI API (Grok)'s 71.7 (BB), and leads in 4 of 7 scored categories. Both do llm inference.", "tasks": [ { "a": "$110", "b": "$21.76", "cheaper": "xai-api", "task": "Research a product and write a sourced report", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, grok-4.7 on xAI API (Grok)" }, { "a": "$25.07", "b": "$4.85", "cheaper": "xai-api", "task": "Build a small four-page website", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, grok-4.7 on xAI API (Grok)" }, { "a": "$5.41", "b": "$1.07", "cheaper": "xai-api", "task": "Find and fix a bug in a large codebase", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, grok-4.7 on xAI API (Grok)" } ], "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.", "xai-api": "Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api", "json": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.min.md" }, "markdown": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against xAI API (Grok)'s 71.7 (BB), and leads in 4 of 7 scored categories. Both do llm inference.\n\n- Azure OpenAI in Foundry Models: grade A, 80/100, rank #14 of 1510. Markdown https://www.anchorterminal.com/tools/azure-openai.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-openai.json\n- xAI API (Grok): grade BB, 71.7/100, rank #152 of 1510. Markdown https://www.anchorterminal.com/tools/xai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/xai-api.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 55\n- Agent ergonomics, 98 against 90\n- Maintenance \u0026 community, 86 against 77\n- Transparency \u0026 trust, 83 against 63\n\nWatch for: Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026\n\n### xAI API (Grok) (BB)\n\nGood for: Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.\n\nWatch for: API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August\n\n\n## Why the edge\n\n### Reliability: Azure OpenAI in Foundry Models +25\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- xAI API (Grok) (55): Status page at status.x.ai with components for the global and US API endpoints, voice, the consumer apps and, since the Cursor merger, Cursor's services, with an RSS feed (20). The feed, read on 6 November, now holds 267 incidents back to 11 August, so the whole 90-day window is readable. On the API components there were high error rates on grok-4.6 and grok-4.5 from 21:57 to 23:28 UTC on 17 August (about 90 minutes) and a models outage on the global and US endpoints from 13:30 to 17:09 UTC on 3 September (about 3 hours 40 minutes), so several majors. A 26-minute datacenter outage across the API on 22 September, voice disruptions of 12 and 28 minutes on 10 September and 6 October, a 63-minute voice and Imagine degradation on 30 October and a 37-second model degradation on 24 October add to the record (0). Rate limits published per model and tier, grok-4.7 at Tier 0 is 150 requests a second and 50M TPM, with the per-second cap derived as RPM divided by 48 (15). The rate-limits page shows exponential backoff on 429, but no Retry-After header or overload guidance was found (10 of 15). No SLA found in the docs or llms.txt (0). The Responses API has been GA since September 2025 and grok-4.7 carries no preview label (10).\n\n### Transparency \u0026 trust: Azure OpenAI in Foundry Models +20\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- xAI API (Grok) (63): Closed service under xAI's enterprise terms, with the Python SDK under Apache-2.0 (15). The docs agree with each other on no training, 30-day abuse retention, 30-day storage of stateful responses and the ZDR route, but the privacy policy, enterprise terms and DPA at x.ai/legal answered a Cloudflare block page on 6 October and again on 6 November, so they couldn't be compared (15 of 30). Dated migration guides and redirect tables for each retirement, but no written deprecation policy, and Chat Completions, Anthropic compatibility and grok-voice-2.0 are labelled deprecated with no date (12 of 20). The US regional endpoint states what stays in the US, the global endpoint guarantees no region, and no subprocessor list was readable (10 of 20).\n\n### Maintenance \u0026 community: Azure OpenAI in Foundry Models +9\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- xAI API (Grok) (77): Model reading. grok-imagine-image-quality and grok-imagine-image-pro retired on 2 November 2026 as announced in September, Grok Voice 3.0 and custom moderation controls in October, Grok 4.7 on 21 September (30). No minimum notice period found. Retirements come as dated migration guides, retired slugs redirect to a replacement rather than failing, billed at the replacement's price, and grok-voice-2.0 was deprecated in October with no end date (4 of 12). Shutdowns in the last 90 days with dates given in advance, `grok-voice-transcribe-1.0` on 2 October and `grok-imagine-image-quality` on 2 November (8 of 8). Release notes several times a month but dated only by month, support by email and a Discord #help channel, not tested. On xai-sdk-python a collaborator commented on 2 of the 16 most recent threads with replies, and most outside pull requests since 23 October are open without a maintainer reply (10 of 15, down from 12). The repository has CI, release and version-bump workflows (5 of 10). One current first-party SDK, `xai-sdk` 1.21.0 tagged on 23 October, Python only (10 of 15). Supported runtimes stated, Python 3.10 or later (10).\n\n### Agent ergonomics: Azure OpenAI in Foundry Models +8\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- xAI API (Grok) (90): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with parallel calls on by default and `tool_choice` of auto, required, none or a named function (20). Guaranteed structured outputs (15). Automatic prompt caching, cached input at 0.25x on grok-4.7 ($0.50 per million) and 0.16x on grok-4.3 (15). 500,000-token context on grok-4.7 and 1,000,000 on grok-4.3, 13 of 15 for the default model's 500K. The Batch API is now 20% off on grok-4.7, 4.6 and 4.5 as well as the older models, with batch requests outside the rate limits (10 of 10, up from 5 on 6 October). One first-party SDK, `xai-sdk` for Python, with the OpenAI SDKs and Vercel's AI SDK documented as alternatives (5 of 10). Status codes documented with fixes, no Retry-After header found (12 of 15).\n\n## Score by category\n\n| Category | Weight | Azure OpenAI in Foundry Models | xAI API (Grok) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 55 | Azure OpenAI in Foundry Models +25 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 87 | 88 | xAI API (Grok) +1 |\n| Agent ergonomics | 13% (16.2 this run) | 98 | 90 | Azure OpenAI in Foundry Models +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 97 | xAI API (Grok) +2 |\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 | 77 | Azure OpenAI in Foundry Models +9 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 83 | 63 | Azure OpenAI in Foundry Models +20 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **80 · A** | **71.7 · BB** | |\n\n## Facts side by side\n\n| Fact | Azure OpenAI in Foundry Models | xAI API (Grok) |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Microsoft | SpaceXSI (xAI) |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | `https://api.x.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Pay per use |\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 service under xAI's enterprise terms of service. The Python SDK is Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-26 | 2026-11-02 |\n| Terms last updated | no date given | 2026-10-27 |\n| Privacy policy last updated | 2026-09-01 | 2026-10-27 |\n| Customer content may train models | yes | yes |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 454k npm/wk | 597 stars, 912k PyPI/wk |\n\n## What the same task costs\n\n| Task | Azure OpenAI in Foundry Models | xAI API (Grok) |\n| --- | --- | --- |\n| Research a product and write a sourced report | $110 | $21.76 |\n| Build a small four-page website | $25.07 | $4.85 |\n| Find and fix a bug in a large codebase | $5.41 | $1.07 |\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**xAI API (Grok).** Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python.\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### xAI API (Grok)\n\n1. Build on the Responses API at https://api.x.ai/v1. Chat Completions is labelled deprecated and the Anthropic-compatible endpoint fully deprecated\n2. Pin a dated model slug. A retired slug keeps answering from a replacement model, billed at the replacement's price\n3. Back off exponentially on 429. The per-second cap is the per-minute budget divided by 48, with a minimum of 2\n4. Set `allowed_tools` on remote MCP servers. There's no approval step, and every exposed tool enters the context\n5. Use https://us.api.x.ai/v1 when processing must stay in the US. It costs 1.1x and serves only grok-4.7 and grok-4.6\n\n## Questions\n\n### Which is better for AI agents, Azure OpenAI in Foundry Models or xAI API (Grok)?\n\nAzure OpenAI in Foundry Models scores 80 (A) on agent readiness against xAI API (Grok)'s 71.7 (BB), and leads in 4 of 7 scored categories.\n\n### Do Azure OpenAI in Foundry Models and xAI API (Grok) need an API key?\n\nAzure OpenAI in Foundry Models takes an API key or an OAuth sign-in. xAI API (Grok) needs an API key.\n\n### Can an agent call Azure OpenAI in Foundry Models and xAI API (Grok) without installing anything?\n\nYes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and xAI API (Grok) at https://api.x.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-openai\", \"b\": \"xai-api\"}`. From a terminal: `anchor compare azure-openai xai-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-openai.json and https://www.anchorterminal.com/api/v1/tools/xai-api.json\n\n## Other comparisons with Azure OpenAI in Foundry Models or xAI API (Grok)\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 xAI API (Grok)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api.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 xAI API (Grok)](https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs xAI API (Grok)](https://www.anchorterminal.com/compare/antseed-vs-xai-api.md)\n- [Azure OpenAI in Foundry Models vs BlockRun.AI](https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.md)\n- [Azure OpenAI in Foundry Models vs Cerebras Inference](https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.md)\n- [Azure OpenAI in Foundry Models vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-ai-gateway.md)\n- [Azure OpenAI in Foundry Models vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-workers-ai.md)\n- [Azure OpenAI in Foundry Models vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat.md)\n- [Azure OpenAI in Foundry Models vs DeepInfra](https://www.anchorterminal.com/compare/azure-openai-vs-deepinfra.md)\n- [Azure OpenAI in Foundry Models vs DeepSeek API](https://www.anchorterminal.com/compare/azure-openai-vs-deepseek-api.md)\n- [Azure OpenAI in Foundry Models vs Eden AI](https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.md)\n- [Azure 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 API](https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api.md)\n- [Azure OpenAI in Foundry Models vs MiniMax API](https://www.anchorterminal.com/compare/azure-openai-vs-minimax-api.md)\n- [Azure OpenAI in Foundry Models vs Mistral AI API](https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api.md)\n- [Azure OpenAI in Foundry Models vs Muse Spark Open](https://www.anchorterminal.com/compare/azure-openai-vs-muse-spark-open.md)\n- [Azure OpenAI in Foundry Models vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/azure-openai-vs-nemotron-3-5-super-vl.md)\n- [Azure OpenAI in Foundry Models vs Novita AI](https://www.anchorterminal.com/compare/azure-openai-vs-novita-ai.md)\n- [Azure OpenAI in Foundry Models vs OpenAI API](https://www.anchorterminal.com/compare/azure-openai-vs-openai-api.md)\n- [Azure OpenAI in Foundry Models vs OpenRouter](https://www.anchorterminal.com/compare/azure-openai-vs-openrouter.md)\n- [Azure OpenAI in Foundry Models vs Prism Inference](https://www.anchorterminal.com/compare/azure-openai-vs-prism-inference.md)\n- [Azure OpenAI in Foundry Models vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/azure-openai-vs-ramp-router.md)\n- [Azure OpenAI in Foundry Models vs Beam 1.0](https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.md)\n- [Azure OpenAI in Foundry Models vs RouterPlus](https://www.anchorterminal.com/compare/azure-openai-vs-routerplus.md)\n- [Azure OpenAI in Foundry Models vs SambaCloud](https://www.anchorterminal.com/compare/azure-openai-vs-sambanova.md)\n- [Azure OpenAI in Foundry Models vs SiliconFlow](https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.md)\n- [Azure OpenAI in Foundry Models vs Simplismart](https://www.anchorterminal.com/compare/azure-openai-vs-simplismart.md)\n- [Azure OpenAI in Foundry Models vs StepFun API](https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api.md)\n- [Azure OpenAI in Foundry Models vs SWE-2 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- [BlockRun.AI vs xAI API (Grok)](https://www.anchorterminal.com/compare/blockrun-ai-vs-xai-api.md)\n- [Cerebras Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/cerebras-inference-vs-xai-api.md)\n- [Cloudflare AI Gateway vs xAI API (Grok)](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-xai-api.md)\n- [Cloudflare Workers AI vs xAI API (Grok)](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-xai-api.md)\n- [Cohere Chat API (Command models) vs xAI API (Grok)](https://www.anchorterminal.com/compare/cohere-chat-vs-xai-api.md)\n- [DeepInfra vs xAI API (Grok)](https://www.anchorterminal.com/compare/deepinfra-vs-xai-api.md)\n- [DeepSeek API vs xAI API (Grok)](https://www.anchorterminal.com/compare/deepseek-api-vs-xai-api.md)\n- [Eden AI vs xAI API (Grok)](https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.md)\n- [Glimpse vs xAI API (Grok)](https://www.anchorterminal.com/compare/elorian-glimpse-vs-xai-api.md)\n- [Fireworks AI Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/fireworks-inference-vs-xai-api.md)\n- [Gemini Developer API vs xAI API (Grok)](https://www.anchorterminal.com/compare/gemini-api-vs-xai-api.md)\n- [GroqCloud vs xAI API (Grok)](https://www.anchorterminal.com/compare/groq-vs-xai-api.md)\n- [Hugging Face Inference Providers vs xAI API (Grok)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api.md)\n- [Inkling 2 Small vs xAI API (Grok)](https://www.anchorterminal.com/compare/inkling-2-small-vs-xai-api.md)\n- [Jais 3 vs xAI API (Grok)](https://www.anchorterminal.com/compare/jais-3-vs-xai-api.md)\n- [Meta Model API vs xAI API (Grok)](https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.md)\n- [MiniMax API vs xAI API (Grok)](https://www.anchorterminal.com/compare/minimax-api-vs-xai-api.md)\n- [Mistral AI API vs xAI API (Grok)](https://www.anchorterminal.com/compare/mistral-api-vs-xai-api.md)\n- [Muse Spark Open vs xAI API (Grok)](https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs xAI API (Grok)](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-xai-api.md)\n- [Novita AI vs xAI API (Grok)](https://www.anchorterminal.com/compare/novita-ai-vs-xai-api.md)\n- [OpenAI API vs xAI API (Grok)](https://www.anchorterminal.com/compare/openai-api-vs-xai-api.md)\n- [OpenRouter vs xAI API (Grok)](https://www.anchorterminal.com/compare/openrouter-vs-xai-api.md)\n- [Prism Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/prism-inference-vs-xai-api.md)\n- [Router.com (Ramp Router) vs xAI API (Grok)](https://www.anchorterminal.com/compare/ramp-router-vs-xai-api.md)\n- [Beam 1.0 vs xAI API (Grok)](https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.md)\n- [RouterPlus vs xAI API (Grok)](https://www.anchorterminal.com/compare/routerplus-vs-xai-api.md)\n- [SambaCloud vs xAI API (Grok)](https://www.anchorterminal.com/compare/sambanova-vs-xai-api.md)\n- [SiliconFlow vs xAI API (Grok)](https://www.anchorterminal.com/compare/siliconflow-vs-xai-api.md)\n- [Simplismart vs xAI API (Grok)](https://www.anchorterminal.com/compare/simplismart-vs-xai-api.md)\n- [StepFun API vs xAI API (Grok)](https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api.md)\n- [SWE-2 Flash vs xAI API (Grok)](https://www.anchorterminal.com/compare/swe-2-flash-vs-xai-api.md)\n- [Tencent Cloud TokenHub vs xAI API (Grok)](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-xai-api.md)\n- [Together AI Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/together-inference-vs-xai-api.md)\n- [Vercel AI Gateway vs xAI API (Grok)](https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api.md)\n- [Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)](https://www.anchorterminal.com/compare/vertex-ai-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 xAI API (Grok)", "url": "" } ], "description": "Azure OpenAI in Foundry Models scores 80 (A) to xAI's 71.7 (BB) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Azure OpenAI in Foundry Models A 80", "xAI API (Grok) BB 71.7", "scores" ], "h1": "Azure OpenAI in Foundry Models vs xAI API (Grok)", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/azure-openai-vs-xai-api", "published": "2026-10-01", "section": "tools", "title": "Azure OpenAI in Foundry Models vs xAI for AI agents (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api" }, "tokens": { "markdown": 6500, "slim": 2930 }, "version": 1 }