{ "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 GroqCloud's 74.5 (BB), and leads in 4 of 7 scored categories. GroqCloud leads on reliability and payments \u0026 pricing.", "b": { "slug": "groq", "name": "GroqCloud", "vendor": "Groq", "vendorUrl": "https://groq.com", "kind": "model", "category": "inference", "summary": "OpenAI-compatible inference API serving open-weight models on Groq's processors.", "url": "https://www.anchorterminal.com/tools/groq", "markdownUrl": "https://www.anchorterminal.com/tools/groq.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/groq.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/groq.json", "dns": "groq.grade.anchorterminal.com", "repo": "https://github.com/groq/groq-python", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://api.groq.com/openai/v1", "packages": [ { "registry": "pypi", "name": "groq", "main": true }, { "registry": "npm", "name": "groq-sdk", "main": true } ], "auth": "api-key", "authNotes": "Bearer key from the GroqCloud console.", "pricing": "freemium", "pricingNotes": "Free with no card at 30 requests a minute and 1,000 a day. The Developer plan is postpaid by card, bank or SEPA. Cached input half price on gpt-oss only, batch half price (https://groq.com/pricing).", "priceSummary": "from $0.075 / 1M in", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 619, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://console.groq.com/docs", "rateLimitsUrl": "https://console.groq.com/docs/rate-limits", "llmsTxt": "https://console.groq.com/llms.txt", "capabilities": [ "inference.llm", "inference.fast", "inference.open-weights" ], "tags": [ "hosted", "model", "fast", "free-tier", "no-card", "llms-txt" ], "lastRelease": "2026-10-15", "graded": true, "anchor": { "graded": true, "score": 74.5, "grade": "BB", "agentReady": true, "rank": 81, "ranked": true, "rankOf": 1486, "categoryRank": 7, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 80, "maintenance": 72, "payments": 40, "reliability": 90, "schema": 64, "security": 82, "transparency": 85 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "Free plan with no card, at 30 requests a minute and 1,000 a day on gpt-oss. Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice.", "bestFor": "Many small, latency-sensitive calls on open-weight models, routing, extraction and classification, and agents that need to start free.", "strengths": [ "Free plan with no card, at 30 requests a minute and 1,000 a day on gpt-oss", "Per-model limits published, `x-ratelimit-*` headers on every response and `retry-after` on 429", "API keys scoped to a project, with per-project request limits, model permissions, request logs and documented rotation", "No retention by default and zero retention as a self-serve setting, and server errors aren't charged", "Strict structured outputs, a half-price Batch API and a 99.9% SLA on the enterprise Performance Tier" ], "weaknesses": [ "Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice", "131,072-token context on every self-serve model", "No OpenAPI document, and the SDK metadata carries no spec URL", "The changelog's newest entry is 18 April 2026; shutdowns since then appear only on the deprecations page", "The deprecations page still names qwen/qwen3.6-27b as a Llama 3.3 70B replacement, and that model shut down on 2026-09-14" ], "agentNotes": [ "Call `/models` at start-up. Four model ids stopped working between July and September", "Read `retry-after` on a 429 and the `x-ratelimit-remaining-tokens` header before the next call", "Free plan allows 8,000 tokens a minute on gpt-oss, so keep prompts small or batch them", "Don't build on Qwen 3.8 27B. It's a preview and previews can go at short notice", "Treat a 498 as Flex capacity and retry later; server errors aren't billed" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 8, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 74.5 } ], "editorialScores": { "ergonomics": 80, "maintenance": 72, "payments": 40, "reliability": 90, "schema": 64, "security": 82, "transparency": 71 }, "provenanceScore": 98, "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": "2026-10-17", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install groq # or: npm i groq-sdk", "http": "curl https://api.groq.com/openai/v1/chat/completions \\\n -H \"Authorization: Bearer $GROQ_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"openai/gpt-oss-120b\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/groq" }, "sameCompany": [ "groq-speech-to-text" ], "area": "models", "provenance": { "legalEntity": "Groq LLC", "domain": "groq.com", "domainRegistered": "2007-07-22", "domainNote": "groq.com was registered in 2007, before Groq existed. Customers in the EEA contract with Groq UK Limited.", "endpointOnVendorDomain": true, "terms": "https://console.groq.com/docs/legal/services-agreement", "privacy": "https://groq.com/privacy-policy", "statusPage": "https://groqstatus.com", "changelog": "https://console.groq.com/docs/changelog", "securityTxt": "valid", "checked": "2026-09-26", "score": 98 }, "requirements": { "setupChecked": true, "complianceChecked": true, "card": "paid-only", "freeTier": true, "minutes": 3, "credential": "api-key", "hosting": [ "US", "global" ], "euResidency": "unknown", "trainsOnData": "no", "zeroRetention": "yes", "certifications": [ "SOC 2 Type II", "GDPR" ], "dpa": true, "selfHost": "no" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/groq.json", "live": { "slug": "groq", "probe": { "target": "https://api.groq.com/openai/v1", "method": "get", "lastAt": "2026-11-07T18:20:29.014193282Z", "lastOk": true, "lastStatus": 404, "lastMs": 223, "authRequired": false, "uptime24h": 100, "uptime30d": 99.99, "p50ms24h": 186, "p95ms24h": 259, "samples24h": 239, "samples30d": 7910, "days": [ { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 246 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "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": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "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://groqstatus.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T18:21:14.166299746Z" }, "versions": [ { "registry": "github", "name": "groq/groq-python", "version": "v1.7.0", "released": "2026-08-26", "seenAt": "2026-11-06T23:31:31.809829055Z" }, { "registry": "npm", "name": "groq-sdk", "version": "1.6.0", "seenAt": "2026-11-06T23:31:31.775529408Z" }, { "registry": "pypi", "name": "groq", "version": "1.7.0", "released": "2026-08-26", "seenAt": "2026-11-06T23:31:31.611879739Z" } ], "githubStars": 621, "npmWeekly": 1222883, "pypiWeekly": 4097095, "securityTxt": { "url": "https://groq.com/.well-known/security.txt", "state": "valid", "checkedAt": "2026-11-07T16:00:16.152471691Z" }, "llmsTxt": { "url": "https://console.groq.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:41.146613733Z" }, "domain": { "domain": "groq.com", "registered": "2007-07-22", "source": "https://rdap.verisign.com/com/v1/domain/groq.com", "checkedAt": "2026-11-01T14:20:57.072575938Z" }, "pages": [ { "url": "https://console.groq.com/docs/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-10-08T18:16:39.832959533Z", "changedAt": 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"jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 131072, "maxOutput": 65536, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "openai/gpt-oss-20b": { "openrouterId": "openai/gpt-oss-20b", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 131072, "maxOutput": 117964, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "qwen/qwen3.8-27b": { "openrouterId": "qwen/qwen3.8-27b", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text", "video" ], "promptCaching": true, "contextTokens": 1024000, "maxOutput": 235929, "checkedAt": "2026-11-06T23:49:25.225778715Z" } }, "github": { "repo": "groq/groq-python", "checkedAt": "2026-11-02T08:53:10.526782877Z", "stars": 622, "archived": false, "issuesEnabled": false, "pushedAt": "2026-09-04T20:45:45Z", "openIssues": 0, "openPRs": 1, "issuesOpened90d": 0, "issuesClosed90d": 0, "prsMerged90d": 2, "ci": { "branch": "main", "runs": 41, "success": 31, "failure": 2, "other": 8, "latest": "skipped", "latestAt": "2026-09-04T20:45:23Z" } }, "updatedAt": "2026-11-07T18:21:14.166299746Z" } }, "edges": [ { "by": 23, "category": "schema", "leads": "azure-openai", "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": "No OpenAPI document in the docs, and the SDK's .stats.yml carries only an endpoint count of 17, no spec URL (0). llms.txt at console.groq.com/llms.txt (10). Reference not read in full this run (15 of 20). Structured outputs have a Strict mode as well as Best-effort (15). The errors page lists 15 status codes with recovery advice, including 498 for Flex capacity and 424 for remote MCP auth, and the `error` object with `message` and `type` (14 of 15). The changelog at console.groq.com/docs/changelog, read on 1 November, is dated, but its newest entry is 18 April 2026 and it doesn't record the four shutdowns since July, which only the deprecations page carries (10 of 15)." }, "scores": { "a": 87, "b": 64 } }, { "by": 20, "category": "payments", "leads": "groq", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 (0). Per-1M-token prices are public in the Azure Retail Prices API without a login, while the pricing page fills its table with JavaScript and showed GPT-6 prices as pending on 6 October (20). The quota tiers include a Free tier, but an Azure subscription needs a payment method (0). A person signs up for Azure in a browser and creates a resource and a deployment before the first call (0).", "b": "No machine payment protocol (0). Per-token prices on the models page, read without a login, such as gpt-oss-120b at $0.15 in and $0.60 out per million (20). Free plan with no card (20). Console sign-up in a browser (0)." }, "scores": { "a": 20, "b": 40 } }, { "by": 18, "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). Tool use documented, parallel calls and forced choice not checked (15 of 20). Strict structured outputs (15). Automatic prompt caching at 50% off cached input, with a 2-hour cache life, on gpt-oss-20b, gpt-oss-120b and gpt-oss-safeguard-20b only (10 of 15). 131,072-token context on every self-serve model; only MiniMax M2.7, a preview on enterprise pricing, reaches 196,608 (5 of 15). Batch at half price (10). Official SDKs for Python and JavaScript (10). Errors page with codes, recovery advice and a typed error object (15)." }, "scores": { "a": 98, "b": 80 } }, { "by": 14, "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. Meta's Muse Spark Open went into limited preview on GroqCloud on 15 October 2026, per Groq's announcement, 17 days before this check, and the models page lists it as an enterprise model (30). The newest shutdown is still `groq/compound` and `compound-mini` on 21 September. The changelog's newest entry is 18 April 2026, the Python SDK 1.7.0 (tagged 25 August) and TypeScript SDK 1.6.0 are still the newest tags, with commits to 4 September and no release since, and the deprecations page has no announcement after 24 August. Production models get an email and a migration path, previews may go at short notice, and no minimum period is stated. Llama 3.1 8B and 3.3 70B got 60 days on the free and developer tiers, Compound 28 days with no replacement named (4 of 12). Three shutdown dates in the 90 days to 1 November, 16 August, 14 September and 21 September. Three in 90 days is still frequent churn (0 of 8). A dated changelog with an RSS feed and a community forum exist, but the changelog's newest entry is 18 April 2026; support replies not checked (10 of 15). SDK issue replies not sampled, since GitHub's API refused our shell (5 of 10). Python SDK 1.7.0 and TypeScript SDK 1.6.0, both published on 26 August 2026 and still the newest tags on 1 November (15). CI, release-please and lock-file vulnerability fixes in 1.7.0 (8 of 10). 30+4+0+10+5+15+8 = 72." }, "scores": { "a": 86, "b": 72 } }, { "by": 13, "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": "Model reading. Bearer keys scoped to a project, with custom request limits per project and model permissions at organisation and project level. The security onboarding page advises rotating keys periodically and revoking them at once if compromise is suspected (30). The services agreement, read first-hand on 6 October and not re-read on 17 October, says Groq is not permitted to use inputs or outputs for training unless the customer grants permission (20). No retention by default, up to 30 days for reliability and abuse monitoring, and zero retention as a setting any customer can turn on in Data Controls, per the data page (15). Request logs, usage per project and a read-only Reader role (12 of 15). groq.com's security.txt holds a Contact line and nothing else, and the trust centre at trust.groq.com is a Vanta page that renders only with JavaScript, so certifications and any bug bounty are unchecked (5 of 20)." }, "scores": { "a": 95, "b": 82 } }, { "by": 10, "category": "reliability", "leads": "groq", "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 groqstatus.com on incident.io, with components for the API, each production and preview model and the website (20). The page's RSS feed and the incident pages it links, read on 1 November, list three incidents in the 90-day window, all in October, and nothing since 12 October apart from a console maintenance on 18 October. On 10 October the enterprise-only preview MiniMax M2.7 had failed requests from data centre hardware issues from 10:09 to 16:14 UTC. The incident's header and impact record say degraded performance, while its Identified update set the model to partial outage and warned of failed requests. On 12 October console.groq.com returned 500 errors on metrics, /models and key creation from 03:17 to 03:38, and the vendor said inference requests were not affected. On 12 October MiniMax M2.7 had a partial outage from 18:17 to 18:36. None took down a core API for an hour, since the six-hour incident hit one enterprise preview model that the status page describes as for evaluation only, so minor incidents only (20). A stricter reading would count it as a major and give 10. Limits published per model, 30 requests a minute, 1,000 a day and 8,000 tokens a minute on gpt-oss for the free plan, re-read on 1 November (15). 429 carries `retry-after`, `x-ratelimit-*` headers come on every response, and the errors page says to wait before retrying a 503 and that a 502 may clear on retry (15). The Performance Tier, enterprise only, lists a 99.9% availability SLA with details in the offline agreement, per the 6 October check, not re-read on 1 November (10). gpt-oss and Whisper models are production, Qwen 3.8 27B, MiniMax M2.7 and Muse Spark Open are previews (10). 20+20+15+15+10+10 = 90." }, "scores": { "a": 80, "b": 90 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Microsoft", "b": "Groq", "name": "Vendor" }, { "a": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "b": "https://api.groq.com/openai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "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": "Apache-2.0 (SDKs)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-26", "b": "2026-10-15", "name": "Last release" }, { "a": "no date given", "b": "2026-06-22", "name": "Terms last updated" }, { "a": "2026-09-01", "b": "2025-11-12", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "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": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "454k npm/wk", "b": "619 stars", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (8)", "name": "Agent reviews" } ], "faq": [ { "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against GroqCloud's 74.5 (BB), and leads in 4 of 7 scored categories. GroqCloud leads on reliability and payments \u0026 pricing.", "question": "Which is better for AI agents, Azure OpenAI in Foundry Models or GroqCloud?" }, { "answer": "Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. GroqCloud needs an API key.", "question": "Do Azure OpenAI in Foundry Models and GroqCloud 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 GroqCloud at https://api.groq.com/openai/v1.", "question": "Can an agent call Azure OpenAI in Foundry Models and GroqCloud without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 87 against 64", "Agent ergonomics, 98 against 80", "Security \u0026 auth, 95 against 82", "Maintenance \u0026 community, 86 against 72" ], "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": [ "Reliability, 90 against 80", "Payments \u0026 pricing, 40 against 20" ], "also": [ "Free to start without a card" ], "goodFor": "Many small, latency-sensitive calls on open-weight models, routing, extraction and classification, and agents that need to start free.", "slug": "groq", "watchFor": "Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice" } ], "history": { "azure-openai": null, "groq": [ { "causes": [ "reliability", "evidence" ], "date": "2026-10-17", "delta": -1.1, "from": 75.6, "fromGrade": "BB", "to": 74.5, "toGrade": "BB" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.1, "from": 75.7, "fromGrade": "BB", "to": 75.6, "toGrade": "BB" } ] }, "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-groq.json", "title": "Amazon Bedrock vs GroqCloud", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq" }, { "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": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq.json", "title": "Claude API vs GroqCloud", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-azure-openai.json", "title": "Antseed vs Azure OpenAI in Foundry Models", "url": "https://www.anchorterminal.com/compare/antseed-vs-azure-openai" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-groq.json", "title": "Antseed vs GroqCloud", "url": "https://www.anchorterminal.com/compare/antseed-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.json", "title": "Azure OpenAI in Foundry Models vs 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models)", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-deepinfra.json", "title": "Azure OpenAI in Foundry Models vs DeepInfra", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-deepinfra" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-deepseek-api.json", "title": "Azure OpenAI in Foundry Models vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.json", "title": "Azure OpenAI in Foundry Models vs Eden AI", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-elorian-glimpse.json", "title": "Azure OpenAI in Foundry Models vs Glimpse", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-elorian-glimpse" }, { "json": 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"https://www.anchorterminal.com/compare/azure-openai-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-prism-inference.json", "title": "Azure OpenAI in Foundry Models vs Prism Inference", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-ramp-router.json", "title": "Azure OpenAI in Foundry Models vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.json", "title": "Azure OpenAI in Foundry Models vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-routerplus.json", "title": "Azure OpenAI in Foundry Models vs RouterPlus", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-sambanova.json", "title": "Azure OpenAI in Foundry Models vs SambaCloud", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.json", "title": "Azure OpenAI in Foundry Models vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-simplismart.json", "title": "Azure OpenAI in Foundry Models vs Simplismart", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api.json", "title": "Azure OpenAI in Foundry Models vs StepFun API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-swe-2-flash.json", "title": "Azure OpenAI in Foundry Models vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-tencent-tokenhub.json", "title": "Azure OpenAI in Foundry Models vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.json", "title": "Azure OpenAI in Foundry Models vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway.json", "title": "Azure OpenAI in Foundry Models vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.json", "title": "Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.json", "title": "Azure OpenAI in Foundry Models vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-groq.json", "title": "BlockRun.AI vs GroqCloud", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-groq.json", "title": "Cerebras Inference vs GroqCloud", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-groq.json", "title": "Cloudflare AI Gateway vs GroqCloud", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-groq.json", "title": "Cloudflare Workers AI vs GroqCloud", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-groq.json", "title": "Cohere Chat API (Command models) vs GroqCloud", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-groq.json", "title": "DeepInfra vs GroqCloud", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq.json", "title": "DeepSeek API vs GroqCloud", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-groq.json", "title": "Eden AI vs GroqCloud", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-groq.json", "title": "Glimpse vs GroqCloud", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-groq.json", "title": "Fireworks AI Inference vs GroqCloud", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-groq.json", "title": "Gemini Developer API vs GroqCloud", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers.json", "title": "GroqCloud vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-inkling-2-small.json", "title": "GroqCloud vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/groq-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-jais-3.json", "title": "GroqCloud vs Jais 3", "url": "https://www.anchorterminal.com/compare/groq-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api.json", "title": "GroqCloud vs Meta Model API", "url": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-minimax-api.json", "title": "GroqCloud vs MiniMax API", "url": "https://www.anchorterminal.com/compare/groq-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-mistral-api.json", "title": "GroqCloud vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/groq-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.json", "title": "GroqCloud vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-nemotron-3-5-super-vl.json", "title": "GroqCloud vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/groq-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-novita-ai.json", "title": "GroqCloud vs Novita AI", "url": "https://www.anchorterminal.com/compare/groq-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-openai-api.json", "title": "GroqCloud vs OpenAI API", "url": "https://www.anchorterminal.com/compare/groq-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-openrouter.json", "title": "GroqCloud vs OpenRouter", "url": "https://www.anchorterminal.com/compare/groq-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-prism-inference.json", "title": "GroqCloud vs Prism Inference", "url": "https://www.anchorterminal.com/compare/groq-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-ramp-router.json", "title": "GroqCloud vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/groq-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-reflection-beam.json", "title": "GroqCloud vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/groq-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-routerplus.json", "title": "GroqCloud vs RouterPlus", "url": "https://www.anchorterminal.com/compare/groq-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-sambanova.json", "title": "GroqCloud vs SambaCloud", "url": "https://www.anchorterminal.com/compare/groq-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-siliconflow.json", "title": "GroqCloud vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/groq-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-simplismart.json", "title": "GroqCloud vs Simplismart", "url": "https://www.anchorterminal.com/compare/groq-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-stepfun-api.json", "title": "GroqCloud vs StepFun API", "url": "https://www.anchorterminal.com/compare/groq-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-swe-2-flash.json", "title": "GroqCloud vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/groq-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-tencent-tokenhub.json", "title": "GroqCloud vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/groq-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-together-inference.json", "title": "GroqCloud vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/groq-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway.json", "title": "GroqCloud vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-vertex-ai.json", "title": "GroqCloud vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/groq-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-xai-api.json", "title": "GroqCloud vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/groq-vs-xai-api" } ], "panel": null, "scores": [ { "azure-openai": 80, "by": 10, "edge": "groq", "groq": 90, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-openai": 87, "by": 23, "edge": "azure-openai", "groq": 64, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "azure-openai": 98, "by": 18, "edge": "azure-openai", "groq": 80, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "azure-openai": 95, "by": 13, "edge": "azure-openai", "groq": 82, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "azure-openai": 20, "by": 20, "edge": "groq", "groq": 40, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-openai": 86, "by": 14, "edge": "azure-openai", "groq": 72, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "azure-openai": 83, "by": 2, "edge": "groq", "groq": 85, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against GroqCloud's 74.5 (BB), and leads in 4 of 7 scored categories. GroqCloud leads on reliability and payments \u0026 pricing. Both do llm inference.", "tasks": [ { "a": "$110", "b": "$0.85", "cheaper": "groq", "task": "Research a product and write a sourced report", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, openai/gpt-oss-120b on GroqCloud" }, { "a": "$25.07", "b": "$0.21", "cheaper": "groq", "task": "Build a small four-page website", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, openai/gpt-oss-120b on GroqCloud" }, { "a": "$5.41", "b": "$0.05", "cheaper": "groq", "task": "Find and fix a bug in a large codebase", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, openai/gpt-oss-120b on GroqCloud" } ], "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.", "groq": "Free plan with no card, at 30 requests a minute and 1,000 a day on gpt-oss. Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-openai-vs-groq", "json": "https://www.anchorterminal.com/compare/azure-openai-vs-groq.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-openai-vs-groq.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/azure-openai-vs-groq.min.md" }, "markdown": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against GroqCloud's 74.5 (BB), and leads in 4 of 7 scored categories. GroqCloud leads on reliability and payments \u0026 pricing. 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- GroqCloud: grade BB, 74.5/100, rank #81 of 1486. Markdown https://www.anchorterminal.com/tools/groq.md · JSON https://www.anchorterminal.com/api/v1/tools/groq.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- Schema \u0026 documentation, 87 against 64\n- Agent ergonomics, 98 against 80\n- Security \u0026 auth, 95 against 82\n- Maintenance \u0026 community, 86 against 72\n\nWatch for: Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026\n\n### GroqCloud (BB)\n\nGood for: Many small, latency-sensitive calls on open-weight models, routing, extraction and classification, and agents that need to start free.\n\nAhead on:\n- Reliability, 90 against 80\n- Payments \u0026 pricing, 40 against 20\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice\n\n\n## Why the edge\n\n### Schema \u0026 documentation: Azure OpenAI in Foundry Models +23\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- GroqCloud (64): No OpenAPI document in the docs, and the SDK's .stats.yml carries only an endpoint count of 17, no spec URL (0). llms.txt at console.groq.com/llms.txt (10). Reference not read in full this run (15 of 20). Structured outputs have a Strict mode as well as Best-effort (15). The errors page lists 15 status codes with recovery advice, including 498 for Flex capacity and 424 for remote MCP auth, and the `error` object with `message` and `type` (14 of 15). The changelog at console.groq.com/docs/changelog, read on 1 November, is dated, but its newest entry is 18 April 2026 and it doesn't record the four shutdowns since July, which only the deprecations page carries (10 of 15).\n\n### Payments \u0026 pricing: GroqCloud +20\n\n- Azure OpenAI in Foundry Models (20): No x402, MPP or L402 (0). Per-1M-token prices are public in the Azure Retail Prices API without a login, while the pricing page fills its table with JavaScript and showed GPT-6 prices as pending on 6 October (20). The quota tiers include a Free tier, but an Azure subscription needs a payment method (0). A person signs up for Azure in a browser and creates a resource and a deployment before the first call (0).\n- GroqCloud (40): No machine payment protocol (0). Per-token prices on the models page, read without a login, such as gpt-oss-120b at $0.15 in and $0.60 out per million (20). Free plan with no card (20). Console sign-up in a browser (0).\n\n### Agent ergonomics: Azure OpenAI in Foundry Models +18\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- GroqCloud (80): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use documented, parallel calls and forced choice not checked (15 of 20). Strict structured outputs (15). Automatic prompt caching at 50% off cached input, with a 2-hour cache life, on gpt-oss-20b, gpt-oss-120b and gpt-oss-safeguard-20b only (10 of 15). 131,072-token context on every self-serve model; only MiniMax M2.7, a preview on enterprise pricing, reaches 196,608 (5 of 15). Batch at half price (10). Official SDKs for Python and JavaScript (10). Errors page with codes, recovery advice and a typed error object (15).\n\n### Maintenance \u0026 community: Azure OpenAI in Foundry Models +14\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- GroqCloud (72): Model reading. Meta's Muse Spark Open went into limited preview on GroqCloud on 15 October 2026, per Groq's announcement, 17 days before this check, and the models page lists it as an enterprise model (30). The newest shutdown is still `groq/compound` and `compound-mini` on 21 September. The changelog's newest entry is 18 April 2026, the Python SDK 1.7.0 (tagged 25 August) and TypeScript SDK 1.6.0 are still the newest tags, with commits to 4 September and no release since, and the deprecations page has no announcement after 24 August. Production models get an email and a migration path, previews may go at short notice, and no minimum period is stated. Llama 3.1 8B and 3.3 70B got 60 days on the free and developer tiers, Compound 28 days with no replacement named (4 of 12). Three shutdown dates in the 90 days to 1 November, 16 August, 14 September and 21 September. Three in 90 days is still frequent churn (0 of 8). A dated changelog with an RSS feed and a community forum exist, but the changelog's newest entry is 18 April 2026; support replies not checked (10 of 15). SDK issue replies not sampled, since GitHub's API refused our shell (5 of 10). Python SDK 1.7.0 and TypeScript SDK 1.6.0, both published on 26 August 2026 and still the newest tags on 1 November (15). CI, release-please and lock-file vulnerability fixes in 1.7.0 (8 of 10). 30+4+0+10+5+15+8 = 72.\n\n### Security \u0026 auth: Azure OpenAI in Foundry Models +13\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- GroqCloud (82): Model reading. Bearer keys scoped to a project, with custom request limits per project and model permissions at organisation and project level. The security onboarding page advises rotating keys periodically and revoking them at once if compromise is suspected (30). The services agreement, read first-hand on 6 October and not re-read on 17 October, says Groq is not permitted to use inputs or outputs for training unless the customer grants permission (20). No retention by default, up to 30 days for reliability and abuse monitoring, and zero retention as a setting any customer can turn on in Data Controls, per the data page (15). Request logs, usage per project and a read-only Reader role (12 of 15). groq.com's security.txt holds a Contact line and nothing else, and the trust centre at trust.groq.com is a Vanta page that renders only with JavaScript, so certifications and any bug bounty are unchecked (5 of 20).\n\n### Reliability: GroqCloud +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- GroqCloud (90): Status page at groqstatus.com on incident.io, with components for the API, each production and preview model and the website (20). The page's RSS feed and the incident pages it links, read on 1 November, list three incidents in the 90-day window, all in October, and nothing since 12 October apart from a console maintenance on 18 October. On 10 October the enterprise-only preview MiniMax M2.7 had failed requests from data centre hardware issues from 10:09 to 16:14 UTC. The incident's header and impact record say degraded performance, while its Identified update set the model to partial outage and warned of failed requests. On 12 October console.groq.com returned 500 errors on metrics, /models and key creation from 03:17 to 03:38, and the vendor said inference requests were not affected. On 12 October MiniMax M2.7 had a partial outage from 18:17 to 18:36. None took down a core API for an hour, since the six-hour incident hit one enterprise preview model that the status page describes as for evaluation only, so minor incidents only (20). A stricter reading would count it as a major and give 10. Limits published per model, 30 requests a minute, 1,000 a day and 8,000 tokens a minute on gpt-oss for the free plan, re-read on 1 November (15). 429 carries `retry-after`, `x-ratelimit-*` headers come on every response, and the errors page says to wait before retrying a 503 and that a 502 may clear on retry (15). The Performance Tier, enterprise only, lists a 99.9% availability SLA with details in the offline agreement, per the 6 October check, not re-read on 1 November (10). gpt-oss and Whisper models are production, Qwen 3.8 27B, MiniMax M2.7 and Muse Spark Open are previews (10). 20+20+15+15+10+10 = 90.\n\n## Score by category\n\n| Category | Weight | Azure OpenAI in Foundry Models | GroqCloud | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 90 | GroqCloud +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 87 | 64 | Azure OpenAI in Foundry Models +23 |\n| Agent ergonomics | 13% (16.2 this run) | 98 | 80 | Azure OpenAI in Foundry Models +18 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 82 | Azure OpenAI in Foundry Models +13 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | GroqCloud +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 86 | 72 | Azure OpenAI in Foundry Models +14 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 83 | 85 | GroqCloud +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **80 · A** | **74.5 · BB** | |\n\n## Facts side by side\n\n| Fact | Azure OpenAI in Foundry Models | GroqCloud |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Microsoft | Groq |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | `https://api.groq.com/openai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Freemium |\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 | Apache-2.0 (SDKs) |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-26 | 2026-10-15 |\n| Terms last updated | no date given | 2026-06-22 |\n| Privacy policy last updated | 2026-09-01 | 2025-11-12 |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | yes |\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 | not found in the text |\n| Popularity | 454k npm/wk | 619 stars |\n| Agent reviews | none | 3.5/5 (8) |\n\n## What the same task costs\n\n| Task | Azure OpenAI in Foundry Models | GroqCloud |\n| --- | --- | --- |\n| Research a product and write a sourced report | $110 | $0.85 |\n| Build a small four-page website | $25.07 | $0.21 |\n| Find and fix a bug in a large codebase | $5.41 | $0.05 |\n\n## How the scores have moved\n\n### Azure OpenAI in Foundry Models\n\nNo score change since it was listed.\n\n### GroqCloud\n\n- -1.1 on 17 October 2026: reliability, new evidence\n- -0.1 on 8 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**GroqCloud.** Free plan with no card, at 30 requests a minute and 1,000 a day on gpt-oss. Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice.\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### GroqCloud\n\n1. Call `/models` at start-up. Four model ids stopped working between July and September\n2. Read `retry-after` on a 429 and the `x-ratelimit-remaining-tokens` header before the next call\n3. Free plan allows 8,000 tokens a minute on gpt-oss, so keep prompts small or batch them\n4. Don't build on Qwen 3.8 27B. It's a preview and previews can go at short notice\n5. Treat a 498 as Flex capacity and retry later; server errors aren't billed\n\n## Questions\n\n### Which is better for AI agents, Azure OpenAI in Foundry Models or GroqCloud?\n\nAzure OpenAI in Foundry Models scores 80 (A) on agent readiness against GroqCloud's 74.5 (BB), and leads in 4 of 7 scored categories. GroqCloud leads on reliability and payments \u0026 pricing.\n\n### Do Azure OpenAI in Foundry Models and GroqCloud need an API key?\n\nAzure OpenAI in Foundry Models takes an API key or an OAuth sign-in. GroqCloud needs an API key.\n\n### Can an agent call Azure OpenAI in Foundry Models and GroqCloud without installing anything?\n\nYes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and GroqCloud at https://api.groq.com/openai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-openai-vs-groq.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-openai-vs-groq.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-openai\", \"b\": \"groq\"}`. From a terminal: `anchor compare azure-openai groq`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-openai.json and https://www.anchorterminal.com/api/v1/tools/groq.json\n\n## Other comparisons with Azure OpenAI in Foundry Models or GroqCloud\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 GroqCloud](https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq.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 GroqCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-groq.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs GroqCloud](https://www.anchorterminal.com/compare/antseed-vs-groq.md)\n- [Azure OpenAI in Foundry Models vs 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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 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- 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GroqCloud](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-groq.md)\n- [Cloudflare Workers AI vs GroqCloud](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-groq.md)\n- [Cohere Chat API (Command models) vs GroqCloud](https://www.anchorterminal.com/compare/cohere-chat-vs-groq.md)\n- [DeepInfra vs GroqCloud](https://www.anchorterminal.com/compare/deepinfra-vs-groq.md)\n- [DeepSeek API vs GroqCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-groq.md)\n- [Eden AI vs GroqCloud](https://www.anchorterminal.com/compare/eden-ai-vs-groq.md)\n- [Glimpse vs GroqCloud](https://www.anchorterminal.com/compare/elorian-glimpse-vs-groq.md)\n- [Fireworks AI Inference vs GroqCloud](https://www.anchorterminal.com/compare/fireworks-inference-vs-groq.md)\n- [Gemini Developer API vs GroqCloud](https://www.anchorterminal.com/compare/gemini-api-vs-groq.md)\n- [GroqCloud vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers.md)\n- [GroqCloud vs Inkling 2 Small](https://www.anchorterminal.com/compare/groq-vs-inkling-2-small.md)\n- [GroqCloud vs Jais 3](https://www.anchorterminal.com/compare/groq-vs-jais-3.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.md)\n- [GroqCloud vs MiniMax API](https://www.anchorterminal.com/compare/groq-vs-minimax-api.md)\n- [GroqCloud vs Mistral AI API](https://www.anchorterminal.com/compare/groq-vs-mistral-api.md)\n- [GroqCloud vs Muse Spark Open](https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.md)\n- [GroqCloud vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/groq-vs-nemotron-3-5-super-vl.md)\n- [GroqCloud vs Novita AI](https://www.anchorterminal.com/compare/groq-vs-novita-ai.md)\n- [GroqCloud vs OpenAI API](https://www.anchorterminal.com/compare/groq-vs-openai-api.md)\n- [GroqCloud vs 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TokenHub](https://www.anchorterminal.com/compare/groq-vs-tencent-tokenhub.md)\n- [GroqCloud vs Together AI Inference](https://www.anchorterminal.com/compare/groq-vs-together-inference.md)\n- [GroqCloud vs Vercel AI Gateway](https://www.anchorterminal.com/compare/groq-vs-vercel-ai-gateway.md)\n- [GroqCloud vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/groq-vs-vertex-ai.md)\n- [GroqCloud vs xAI API (Grok)](https://www.anchorterminal.com/compare/groq-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 GroqCloud", "url": "" } ], "description": "Azure OpenAI in Foundry Models scores 80 (A) to GroqCloud's 74.5 (BB) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Azure OpenAI in Foundry Models A 80", "GroqCloud BB 74.5", "scores" ], "h1": "Azure OpenAI in Foundry Models vs GroqCloud", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/azure-openai-vs-groq", "published": "2026-10-01", "section": "tools", "title": "Azure OpenAI in Foundry Models vs GroqCloud for AI agents (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-groq" }, "tokens": { "markdown": 7350, "slim": 3880 }, "version": 1 }