{ "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 SiliconFlow's 42.9 (E), and leads in 6 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing.", "b": { "slug": "siliconflow", "name": "SiliconFlow", "vendor": "SiliconFlow Labs Pte. Ltd.", "vendorUrl": "https://www.siliconflow.com", "kind": "model", "category": "inference", "summary": "SiliconFlow is a hosted inference API for open-weight models, covering chat, vision, embeddings, reranking, image, video and speech. It answers OpenAI-style and Anthropic-style calls at api.siliconflow.com with a Bearer key.", "url": "https://www.anchorterminal.com/tools/siliconflow", "markdownUrl": "https://www.anchorterminal.com/tools/siliconflow.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/siliconflow.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/siliconflow.json", "dns": "siliconflow.grade.anchorterminal.com", "license": "Proprietary service under the SiliconFlow Terms of Use", "transports": [ "http" ], "remoteUrl": "https://api.siliconflow.com/v1", "packages": [], "auth": "api-key", "authNotes": "Self-serve Bearer key from the console at https://cloud.siliconflow.com/account/ak after a browser sign-up with a Google or GitHub account. The Anthropic-style `/messages` route also takes the key in `x-api-key`. No scopes, expiry or per-key limits are documented, and rate limits apply to the account, not the key. The error page says some models answer 403 until real-name authentication is done.", "pricing": "usage", "pricingNotes": "Pay per token, image, video or byte of speech text, with $1 in free credits for a new account. Whether a card is needed to claim the credit was not established. DeepSeek-V4.1-Flash costs $0.15 in, $0.003 cached and $0.60 out per 1M tokens. The FAQ says monthly spending limits can be set in the dashboard (https://www.siliconflow.com/pricing, checked 2026-10-09).", "priceSummary": "from $0.15 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI file or the pricing page (checked 2026-10-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://docs.siliconflow.com/en/userguide/quickstart", "rateLimitsUrl": "https://docs.siliconflow.com/cn/userguide/rate-limits/rate-limit-and-upgradation", "llmsTxt": "https://docs.siliconflow.com/llms.txt", "openapi": "https://docs.siliconflow.com/cn/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights", "embed.text", "rerank", "image.generate", "video.generate", "speech.tts", "speech.stt" ], "tags": [ "hosted", "model", "open-weights", "usage-based", "free-credit", "openapi", "llms-txt", "openai-compatible", "anthropic-compatible", "singapore" ], "lastRelease": "2026-09-14", "graded": true, "anchor": { "graded": true, "score": 42.9, "grade": "E", "agentReady": false, "rank": 1248, "ranked": true, "rankOf": 1486, "categoryRank": 39, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 60, "maintenance": 37, "payments": 35, "reliability": 33, "schema": 65, "security": 39, "transparency": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-05" }, "negative": -3, "negativeNotes": [ "2025-12-31 to 2026-06-11. SiliconFlow's release notes carry six model removal entries dated the day the models were removed, with no earlier entry announcing them, and on 11 June 2026 all traffic for `zai-org/GLM-5` and `moonshotai/Kimi-K2.5` was routed to successor models in an entry of the same date. Requests naming those models stopped working or changed model with notice only on the day. Read at the floor and folded into one term, as together-inference's and fireworks-inference's same-day serverless removals were, -3 (https://docs.siliconflow.com/en/release-notes/overview, per the 9 October reading)." ], "verdict": "Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice.", "bestFor": "Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.", "strengths": [ "Per-token, per-image and per-video prices are public for every listed model, such as DeepSeek-V4.1-Flash at $0.15 in and $0.60 out per 1M tokens", "One Bearer key reaches 22 operations in a public OpenAPI 3.0 file, with OpenAI-style `/chat/completions` and Anthropic-style `/messages`", "`llms.txt` and a Markdown copy of every docs page, in English and Chinese", "Rate limits are published by spend tier, from 1,000 requests and 40,000 tokens a minute at L0 to 10,000 and 2,000,000 at L5", "The terms say SiliconFlow will not access Interaction Data, has no obligation to store it, and uses it only to supply the service" ], "weaknesses": [ "No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment", "Release notes stop at 11 June 2026. Six notices from December 2025 to June 2026 give a removal date equal to the notice date", "The Terms of Use of 9 September 2026 forbid use for any commercial purposes, scraping tools and benchmarking. This matters before any probe is run", "The OpenAPI model list and the function calling guide name models already removed, and omit every model added since July 2026", "No security.txt, disclosure policy, certification, DPA or sub-processor list was found, and no official SDK is published" ], "agentNotes": [ "Set the OpenAI client's base URL to `https://api.siliconflow.com/v1`, or the Anthropic client's to `https://api.siliconflow.com/`, and send the key as a Bearer token", "Take model ids from the model pages or `GET /v1/models`, not from the OpenAPI enum or the function calling guide, which list removed models", "Check the `model` field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models", "Use `response_format` of `json_object` only where the model page says JSON Mode is supported, and keep `max_tokens` about 10,000 below the context length", "Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 42.9 } ], "editorialScores": { "ergonomics": 60, "maintenance": 37, "payments": 35, "reliability": 33, "schema": 65, "security": 39, "transparency": 34 }, "provenanceScore": 70, "checked": { "categories": { "ergonomics": "2026-11-05", "maintenance": "2026-11-05", "payments": "2026-11-05", "reliability": "2026-11-05", "schema": "2026-11-05", "security": "2026-11-05", "transparency": "2026-11-05" }, "last": "2026-11-05", "lastMoved": "2026-11-05", "oldest": "2026-11-05", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install --upgrade openai", "http": "curl --request POST \\\n --url https://api.siliconflow.com/v1/chat/completions \\\n --header 'authorization: Bearer $SILICONFLOW_API_KEY' \\\n --header 'content-type: application/json' \\\n --data '{\"model\":\"deepseek-ai/DeepSeek-V4.1-Flash\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}],\"max_tokens\":128}'", "claudeCode": "export ANTHROPIC_BASE_URL=\"https://api.siliconflow.com/\"\nexport ANTHROPIC_MODEL=\"your-preferred-model\"\nexport ANTHROPIC_API_KEY=\"sk-your-api-key-here\"" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/siliconflow" }, "area": "models", "unitPrices": [ { "item": "Z-Image-Turbo, one image", "unit": "image", "usd": 0.005 }, { "item": "FLUX.1-dev, one image", "unit": "image", "usd": 0.014 }, { "item": "FLUX 1.1 [pro], one image", "unit": "image", "usd": 0.04 }, { "item": "Wan2.2-T2V-A14B, one video", "unit": "call", "usd": 0.29, "note": "Priced per video generated" } ], "provenance": { "legalEntity": "SiliconFlow Labs Pte. Ltd.", "domain": "siliconflow.com", "domainRegistered": "2019-02-14", "endpointOnVendorDomain": true, "terms": "https://docs.siliconflow.com/en/legals/terms-of-service", "privacy": "https://docs.siliconflow.com/en/legals/privacy-policy", "statusPage": "", "changelog": "https://docs.siliconflow.com/en/release-notes/overview", "securityTxt": "none", "checked": "2026-11-05", "notes": [ "The Terms of Use, updated 9 September 2026, name SILICONFLOW LABS PTE. LTD., apply Singapore law and set SIAC arbitration in Singapore. They govern the platform in its web, API and mobile versions, and no separate API agreement was found.", "The Privacy Policy, updated 9 September 2026, names the same entity and cites Singapore's Personal Data Protection Act 2012. It keeps square brackets around several values, such as [Stripe] and [Google and GitHub].", "No status page is linked from the site, the docs index or the pages read.", "https://www.siliconflow.com/.well-known/security.txt answered 404.", "The API answers at api.siliconflow.com, the docs at docs.siliconflow.com and the console at cloud.siliconflow.com. The terms point users in mainland China to siliconflow.cn.", "No SLA, DPA or sub-processor list was found.", "The Terms of Use (updated 9 September 2026) clause 3.4(i) bar any manual or automated software, including spiders, robots, scrapers and crawlers, to scrape, collect or download information from the Platform or Services, which they define to include the web, API and mobile versions (read 5 November 2026).", "The domain registration date was recorded from an RDAP lookup on 9 October 2026, a source this check doesn't use. It wasn't re-read." ], "score": 70 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/siliconflow.json", "live": { "slug": "siliconflow", "probe": { "target": "https://api.siliconflow.com/v1", "method": "get", "lastAt": "2026-11-07T18:20:54.611492377Z", "lastOk": true, "lastStatus": 404, "lastMs": 347, "authRequired": false, "uptime24h": 100, "uptime30d": 99.99, "p50ms24h": 278, "p95ms24h": 381, "samples24h": 239, "samples30d": 7205, "days": [ { "date": "2026-10-09", "probes": 85, "ok": 85 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "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": 252 }, { "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": 250, "ok": 250 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "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 } ] }, "securityTxt": { "url": "https://siliconflow.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:29.327038169Z" }, "llmsTxt": { "url": "https://docs.siliconflow.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:55.35975587Z" }, "domain": { "domain": "siliconflow.com", "registered": "2019-02-14", "source": "https://rdap.verisign.com/com/v1/domain/siliconflow.com", "checkedAt": "2026-11-01T14:18:54.160809284Z" }, "pages": [ { "url": "https://docs.siliconflow.com/en/release-notes/overview", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:08:02.877282346Z", "changedAt": "2026-10-26T03:15:35.683654862Z", "fingerprint": "174b36f1f0c8" }, { "url": "https://www.siliconflow.com/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-11-07T14:34:38.076372647Z", "changedAt": "2026-10-22T01:36:57.039692841Z", "fingerprint": "e1314294f4a8" }, { "url": "https://docs.siliconflow.com/en/legals/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:07:58.655668132Z", "changedAt": "2026-10-26T03:15:31.436126122Z", "fingerprint": "6533065904d9" }, { "url": "https://docs.siliconflow.com/en/legals/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:08:00.852123613Z", "changedAt": "2026-10-26T03:15:33.589043532Z", "fingerprint": "9b70022b01e3" } ], "updatedAt": "2026-11-07T18:20:54.611492377Z" } }, "edges": [ { "by": 56, "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": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Bearer keys created in the console. No scopes, expiry, per-key limits or rotation are documented, and deletion of a key was not confirmed because the console was not read (15 of 30). The terms say Interaction Data is used only to supply the service and is not used or disclosed without authorisation. No statement on model training was found (12 of 20). The terms say there is no obligation to store Interaction Data. No retention period or zero-retention option is stated, and clause 5.11 allows communications to be recorded and passed to the authorities (6 of 15). The release note of 26 March 2026 describes usage and cost breakdowns and invoice export, and the pricing FAQ says monthly spending limits can be set. No audit log was found (6 of 15). No security.txt (404), disclosure policy, bug bounty or named certification was found on the pages read. The product introduction says the service complies with industry standards and names none (0 of 20). 15+12+6+6+0 = 39." }, "scores": { "a": 95, "b": 39 } }, { "by": 49, "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": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Model reading, per the 9 October check, not re-read on 5 November. Hy4-preview is listed as released on 14 September 2026, 52 days before this check, and no later model or API change was recorded; blog post dates record no API change (20). No notice period is stated. Six removal notices from 31 December 2025 to 11 June 2026 are dated the day of removal, and two in March 2026 gave six and seven days (2 of 12). The release notes record about 60 model ids removed in ten notices over the last twelve months (2 of 8). The release notes stop at 11 June 2026 while nine chat models were added afterwards. Support is by email and Discord (6 of 15). Replies in the support channels were not examined (2 of 10). No official SDK. The `langchain-siliconflow` repository in the vendor's GitHub organisation was last changed on 12 December 2025 (version 0.2.3), confirmed from a clone on 5 November (3 of 15). The API description and two guides are out of date (2 of 10). 20+2+2+6+2+3+2 = 37." }, "scores": { "a": 86, "b": 37 } }, { "by": 47, "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": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Hosted reading. No status page is linked from the site, the docs index or any page read (0). With no page there is no incident record to read (5 of 30). Rate limits are published with numbers by spend tier, from 1,000 requests and 40,000 tokens a minute at L0 to 10,000 and 2,000,000 at L5, on a page served only in Chinese, with per-model figures left to the console (12 of 15). The 429 body is documented and names the limit reached, and the docs say to wait and retry. No `Retry-After` header, backoff figures or idempotency guidance were found (6 of 15). No SLA found. Clause 4.2 of the terms disclaims any uptime or availability commitment (0). The serverless API is generally available, and `/systemone` is marked alpha (10). 0+5+12+6+0+10 = 33." }, "scores": { "a": 80, "b": 33 } }, { "by": 38, "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": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). OpenAI-style `tools` with up to 128 functions, and each model page says whether Tools are supported. No `tool_choice` field is in the chat schema and the guide is out of date (12 of 20). `response_format` of `json_object`. The DeepSeek-V4.1-Flash page says Structured Outputs are not supported (7 of 15). Cached input prices are published per model. No caching guide was found (8 of 15). Context listed as 1049K tokens on eleven chat models on the home page, with output up to 393K (14 of 15). `/files` and `/batches` are in the OpenAPI file for chat completions only, with no guide in the English index, no batch price and a window description that contradicts itself (5 of 10). No official SDK. The OpenAI and Anthropic clients work with a changed base URL (6 of 10). Errors carry an HTTP status, a numeric code and a message. No list of codes was found (8 of 15). 12+7+8+14+5+6+8 = 60." }, "scores": { "a": 98, "b": 60 } }, { "by": 31, "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": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Closed service. The Terms of Use name the entity, Singapore law and SIAC arbitration. They also grant a licence \"for in Singapore\" and forbid use for any commercial purposes, which sits oddly with a paid API (10 of 30). The terms and the privacy policy agree that Interaction Data is processed on the customer's instructions with no obligation to store it. No retention period or DPA was found, and the privacy policy keeps drafting brackets around several values (12 of 30). Dated removal notices in the release notes, with no written policy or notice period (8 of 20). Stripe is named as payment processor and other providers only by type. Data may be handled within or outside Singapore, with no locations given (4 of 20). 10+12+8+4 = 34." }, "scores": { "a": 83, "b": 52 } }, { "by": 22, "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": "SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Public OpenAPI 3.0 file with 22 operations and 102 schemas, linked from `llms.txt` under the Chinese path only. Its chat model enum of 71 ids includes removed models and omits every model added since July 2026 (19 of 25). `llms.txt` and a Markdown copy of each docs page (10). Guides for function calling, JSON mode, reasoning, prefix and FIM completion. The function calling guide lists only models the release notes show as removed, and its examples use DeepSeek-V2.5 (10 of 20). Typed parameters with 104 enums and required fields. `response_format` is typed as a bare string with an example (10 of 15). Curl and Python examples, an error page with seven HTTP codes and one body code, and 400, 401, 404, 429, 503 and 504 responses in the file (9 of 15). The file's version reads 1.0.0. The release notes are dated, stop at 11 June 2026 and since March 2026 record only model removals (7 of 15). 19+10+10+10+9+7 = 65." }, "scores": { "a": 87, "b": 65 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Microsoft", "b": "SiliconFlow Labs Pte. Ltd.", "name": "Vendor" }, { "a": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "b": "https://api.siliconflow.com/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 the SiliconFlow Terms of Use", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-26", "b": "2026-09-14", "name": "Last release" }, { "a": "no date given", "b": "no date given", "name": "Terms last updated" }, { "a": "2026-09-01", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "yes", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "yes", "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": "none", "name": "Popularity" }, { "a": "none", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against SiliconFlow's 42.9 (E), and leads in 6 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Azure OpenAI in Foundry Models or SiliconFlow?" }, { "answer": "Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. SiliconFlow needs an API key.", "question": "Do Azure OpenAI in Foundry Models and SiliconFlow 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 SiliconFlow at https://api.siliconflow.com/v1.", "question": "Can an agent call Azure OpenAI in Foundry Models and SiliconFlow without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 80 against 33", "Schema \u0026 documentation, 87 against 65", "Agent ergonomics, 98 against 60", "Security \u0026 auth, 95 against 39", "Maintenance \u0026 community, 86 against 37", "Transparency \u0026 trust, 83 against 52" ], "also": [ "Agent-ready, a grade of BB or better", "No incidents deducted, where SiliconFlow loses 3 points for them" ], "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": [ "Payments \u0026 pricing, 35 against 20" ], "also": null, "goodFor": "Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.", "slug": "siliconflow", "watchFor": "No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment" } ], "history": { "azure-openai": null, "siliconflow": [ { "causes": [ "correction", "time" ], "date": "2026-11-05", "delta": -3.9, "from": 46.8, "fromGrade": "D", "to": 42.9, "toGrade": "E" }, { "causes": [ "correction" ], "date": "2026-10-28", "delta": -0.2, "from": 47, "fromGrade": "D", "to": 46.8, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.3, "from": 46.7, "fromGrade": "D", "to": 47, "toGrade": "D" } ] }, "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-siliconflow.json", "title": "Amazon Bedrock vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow" }, { "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-siliconflow.json", "title": "Claude API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow" }, { "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-siliconflow.json", "title": "Antseed vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/antseed-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.json", "title": "Azure OpenAI in Foundry Models vs BlockRun.AI", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.json", "title": "Azure OpenAI in Foundry Models vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-ai-gateway.json", "title": "Azure OpenAI in Foundry Models vs Cloudflare AI Gateway", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-workers-ai.json", "title": "Azure OpenAI in Foundry Models vs Cloudflare Workers AI", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-workers-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat.json", "title": "Azure OpenAI in Foundry Models vs Cohere Chat API (Command 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": "https://www.anchorterminal.com/compare/azure-openai-vs-fireworks-inference.json", "title": "Azure OpenAI in Foundry Models vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-gemini-api.json", "title": "Azure OpenAI in Foundry Models vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-groq.json", "title": "Azure OpenAI in Foundry Models vs GroqCloud", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.json", "title": "Azure OpenAI in Foundry Models vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small.json", "title": "Azure OpenAI in Foundry Models vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-jais-3.json", "title": "Azure OpenAI in Foundry Models vs Jais 3", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api.json", "title": "Azure OpenAI in Foundry Models vs Meta Model API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-minimax-api.json", "title": "Azure OpenAI in Foundry Models vs MiniMax API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api.json", "title": "Azure OpenAI in Foundry Models vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-muse-spark-open.json", "title": "Azure OpenAI in Foundry Models vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-nemotron-3-5-super-vl.json", "title": "Azure OpenAI in Foundry Models vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-novita-ai.json", "title": "Azure OpenAI in Foundry Models vs Novita AI", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-openai-api.json", "title": "Azure OpenAI in Foundry Models vs OpenAI API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-openrouter.json", "title": "Azure OpenAI in Foundry Models vs OpenRouter", "url": "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-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-siliconflow.json", "title": "BlockRun.AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow.json", "title": "Cerebras Inference vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow.json", "title": "Cloudflare AI Gateway vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow.json", "title": "Cloudflare Workers AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow.json", "title": "Cohere Chat API (Command models) vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow.json", "title": "DeepInfra vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.json", "title": "DeepSeek API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.json", "title": "Eden AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-siliconflow.json", "title": "Glimpse vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow.json", "title": "Fireworks AI Inference vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.json", "title": "Gemini Developer API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow" }, { "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/hugging-face-inference-providers-vs-siliconflow.json", "title": "Hugging Face Inference Providers vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-siliconflow.json", "title": "Inkling 2 Small vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-siliconflow.json", "title": "Jais 3 vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/jais-3-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json", "title": "Meta Model API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow.json", "title": "MiniMax API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.json", "title": "Mistral AI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.json", "title": "Muse Spark Open vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.json", "title": "Novita AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.json", "title": "OpenAI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow.json", "title": "OpenRouter vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow.json", "title": "Prism Inference vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-siliconflow.json", "title": "Router.com (Ramp Router) vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.json", "title": "Beam 1.0 vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-siliconflow.json", "title": "RouterPlus vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/routerplus-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.json", "title": "SambaCloud vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-simplismart.json", "title": "SiliconFlow vs Simplismart", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api.json", "title": "SiliconFlow vs StepFun API", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-swe-2-flash.json", "title": "SiliconFlow vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-tencent-tokenhub.json", "title": "SiliconFlow vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-together-inference.json", "title": "SiliconFlow vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway.json", "title": "SiliconFlow vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai.json", "title": "SiliconFlow vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-vertex-ai" }, { "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/nemotron-3-5-super-vl-vs-siliconflow.json", "title": "Nemotron 3.5 Super VL vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-siliconflow" } ], "panel": null, "scores": [ { "azure-openai": 80, "by": 47, "edge": "azure-openai", "key": "reliability", "name": "Reliability", "siliconflow": 33, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-openai": 87, "by": 22, "edge": "azure-openai", "key": "schema", "name": "Schema \u0026 documentation", "siliconflow": 65, "weight": 13 }, { "azure-openai": 98, "by": 38, "edge": "azure-openai", "key": "ergonomics", "name": "Agent ergonomics", "siliconflow": 60, "weight": 13 }, { "azure-openai": 95, "by": 56, "edge": "azure-openai", "key": "security", "name": "Security \u0026 auth", "siliconflow": 39, "weight": 14 }, { "azure-openai": 20, "by": 15, "edge": "siliconflow", "key": "payments", "name": "Payments \u0026 pricing", "siliconflow": 35, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-openai": 86, "by": 49, "edge": "azure-openai", "key": "maintenance", "name": "Maintenance \u0026 community", "siliconflow": 37, "weight": 7 }, { "azure-openai": 83, "by": 31, "edge": "azure-openai", "key": "transparency", "name": "Transparency \u0026 trust", "siliconflow": 52, "weight": 7 } ], "summary": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against SiliconFlow's 42.9 (E), and leads in 6 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing. Both do llm inference.", "tasks": [ { "a": "$110", "b": "$0.09", "cheaper": "siliconflow", "task": "Research a product and write a sourced report", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, deepseek-ai/DeepSeek-V4.1-Flash on SiliconFlow" }, { "a": "$25.07", "b": "$0.05", "cheaper": "siliconflow", "task": "Build a small four-page website", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, deepseek-ai/DeepSeek-V4.1-Flash on SiliconFlow" }, { "a": "$5.41", "b": "$0.01", "cheaper": "siliconflow", "task": "Find and fix a bug in a large codebase", "what": "gpt-6-astra on Azure OpenAI in Foundry Models, deepseek-ai/DeepSeek-V4.1-Flash on SiliconFlow" } ], "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.", "siliconflow": "Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow", "json": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.min.md" }, "markdown": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against SiliconFlow's 42.9 (E), and leads in 6 of 7 scored categories. SiliconFlow leads on 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- SiliconFlow: grade E, 42.9/100, rank #1248 of 1486. Markdown https://www.anchorterminal.com/tools/siliconflow.md · JSON https://www.anchorterminal.com/api/v1/tools/siliconflow.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 33\n- Schema \u0026 documentation, 87 against 65\n- Agent ergonomics, 98 against 60\n- Security \u0026 auth, 95 against 39\n- Maintenance \u0026 community, 86 against 37\n- Transparency \u0026 trust, 83 against 52\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- No incidents deducted, where SiliconFlow loses 3 points for them\n\nWatch for: Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026\n\n### SiliconFlow (E)\n\nGood for: Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.\n\nAhead on:\n- Payments \u0026 pricing, 35 against 20\n\nWatch for: No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment\n\n\n## Why the edge\n\n### Security \u0026 auth: Azure OpenAI in Foundry Models +56\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- SiliconFlow (39): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Bearer keys created in the console. No scopes, expiry, per-key limits or rotation are documented, and deletion of a key was not confirmed because the console was not read (15 of 30). The terms say Interaction Data is used only to supply the service and is not used or disclosed without authorisation. No statement on model training was found (12 of 20). The terms say there is no obligation to store Interaction Data. No retention period or zero-retention option is stated, and clause 5.11 allows communications to be recorded and passed to the authorities (6 of 15). The release note of 26 March 2026 describes usage and cost breakdowns and invoice export, and the pricing FAQ says monthly spending limits can be set. No audit log was found (6 of 15). No security.txt (404), disclosure policy, bug bounty or named certification was found on the pages read. The product introduction says the service complies with industry standards and names none (0 of 20). 15+12+6+6+0 = 39.\n\n### Maintenance \u0026 community: Azure OpenAI in Foundry Models +49\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- SiliconFlow (37): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Model reading, per the 9 October check, not re-read on 5 November. Hy4-preview is listed as released on 14 September 2026, 52 days before this check, and no later model or API change was recorded; blog post dates record no API change (20). No notice period is stated. Six removal notices from 31 December 2025 to 11 June 2026 are dated the day of removal, and two in March 2026 gave six and seven days (2 of 12). The release notes record about 60 model ids removed in ten notices over the last twelve months (2 of 8). The release notes stop at 11 June 2026 while nine chat models were added afterwards. Support is by email and Discord (6 of 15). Replies in the support channels were not examined (2 of 10). No official SDK. The `langchain-siliconflow` repository in the vendor's GitHub organisation was last changed on 12 December 2025 (version 0.2.3), confirmed from a clone on 5 November (3 of 15). The API description and two guides are out of date (2 of 10). 20+2+2+6+2+3+2 = 37.\n\n### Reliability: Azure OpenAI in Foundry Models +47\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- SiliconFlow (33): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Hosted reading. No status page is linked from the site, the docs index or any page read (0). With no page there is no incident record to read (5 of 30). Rate limits are published with numbers by spend tier, from 1,000 requests and 40,000 tokens a minute at L0 to 10,000 and 2,000,000 at L5, on a page served only in Chinese, with per-model figures left to the console (12 of 15). The 429 body is documented and names the limit reached, and the docs say to wait and retry. No `Retry-After` header, backoff figures or idempotency guidance were found (6 of 15). No SLA found. Clause 4.2 of the terms disclaims any uptime or availability commitment (0). The serverless API is generally available, and `/systemone` is marked alpha (10). 0+5+12+6+0+10 = 33.\n\n### Agent ergonomics: Azure OpenAI in Foundry Models +38\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- SiliconFlow (60): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). OpenAI-style `tools` with up to 128 functions, and each model page says whether Tools are supported. No `tool_choice` field is in the chat schema and the guide is out of date (12 of 20). `response_format` of `json_object`. The DeepSeek-V4.1-Flash page says Structured Outputs are not supported (7 of 15). Cached input prices are published per model. No caching guide was found (8 of 15). Context listed as 1049K tokens on eleven chat models on the home page, with output up to 393K (14 of 15). `/files` and `/batches` are in the OpenAPI file for chat completions only, with no guide in the English index, no batch price and a window description that contradicts itself (5 of 10). No official SDK. The OpenAI and Anthropic clients work with a changed base URL (6 of 10). Errors carry an HTTP status, a numeric code and a message. No list of codes was found (8 of 15). 12+7+8+14+5+6+8 = 60.\n\n### Transparency \u0026 trust: Azure OpenAI in Foundry Models +31\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- SiliconFlow (52): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Closed service. The Terms of Use name the entity, Singapore law and SIAC arbitration. They also grant a licence \"for in Singapore\" and forbid use for any commercial purposes, which sits oddly with a paid API (10 of 30). The terms and the privacy policy agree that Interaction Data is processed on the customer's instructions with no obligation to store it. No retention period or DPA was found, and the privacy policy keeps drafting brackets around several values (12 of 30). Dated removal notices in the release notes, with no written policy or notice period (8 of 20). Stripe is named as payment processor and other providers only by type. Data may be handled within or outside Singapore, with no locations given (4 of 20). 10+12+8+4 = 34.\n\n### Schema \u0026 documentation: Azure OpenAI in Foundry Models +22\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- SiliconFlow (65): SiliconFlow's Terms of Use bar spiders, robots, scrapers and crawlers on the Platform, so its sites were not re-read on 5 November. Per the 9 October check, not re-read on 5 November. Model reading. Public OpenAPI 3.0 file with 22 operations and 102 schemas, linked from `llms.txt` under the Chinese path only. Its chat model enum of 71 ids includes removed models and omits every model added since July 2026 (19 of 25). `llms.txt` and a Markdown copy of each docs page (10). Guides for function calling, JSON mode, reasoning, prefix and FIM completion. The function calling guide lists only models the release notes show as removed, and its examples use DeepSeek-V2.5 (10 of 20). Typed parameters with 104 enums and required fields. `response_format` is typed as a bare string with an example (10 of 15). Curl and Python examples, an error page with seven HTTP codes and one body code, and 400, 401, 404, 429, 503 and 504 responses in the file (9 of 15). The file's version reads 1.0.0. The release notes are dated, stop at 11 June 2026 and since March 2026 record only model removals (7 of 15). 19+10+10+10+9+7 = 65.\n\n## Score by category\n\n| Category | Weight | Azure OpenAI in Foundry Models | SiliconFlow | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 33 | Azure OpenAI in Foundry Models +47 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 87 | 65 | Azure OpenAI in Foundry Models +22 |\n| Agent ergonomics | 13% (16.2 this run) | 98 | 60 | Azure OpenAI in Foundry Models +38 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 39 | Azure OpenAI in Foundry Models +56 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 35 | SiliconFlow +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 86 | 37 | Azure OpenAI in Foundry Models +49 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 83 | 52 | Azure OpenAI in Foundry Models +31 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **80 · A** | **42.9 · E** | |\n\n## Facts side by side\n\n| Fact | Azure OpenAI in Foundry Models | SiliconFlow |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Microsoft | SiliconFlow Labs Pte. Ltd. |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | `https://api.siliconflow.com/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 the SiliconFlow Terms of Use |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-26 | 2026-09-14 |\n| Terms last updated | no date given | no date given |\n| Privacy policy last updated | 2026-09-01 | no date given |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 454k npm/wk | none |\n| Agent reviews | none | 2.5/5 (4) |\n\n## What the same task costs\n\n| Task | Azure OpenAI in Foundry Models | SiliconFlow |\n| --- | --- | --- |\n| Research a product and write a sourced report | $110 | $0.09 |\n| Build a small four-page website | $25.07 | $0.05 |\n| Find and fix a bug in a large codebase | $5.41 | $0.01 |\n\n## How the scores have moved\n\n### Azure OpenAI in Foundry Models\n\nNo score change since it was listed.\n\n### SiliconFlow\n\n- -3.9 on 5 November 2026 (D to E): correction, time\n- -0.2 on 28 October 2026: correction\n- +0.3 on 27 October 2026: checklist\n\n## Verdicts\n\n**Azure OpenAI in Foundry Models.** An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.\n\n**SiliconFlow.** Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their 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### SiliconFlow\n\n1. Set the OpenAI client's base URL to `https://api.siliconflow.com/v1`, or the Anthropic client's to `https://api.siliconflow.com/`, and send the key as a Bearer token\n2. Take model ids from the model pages or `GET /v1/models`, not from the OpenAPI enum or the function calling guide, which list removed models\n3. Check the `model` field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models\n4. Use `response_format` of `json_object` only where the model page says JSON Mode is supported, and keep `max_tokens` about 10,000 below the context length\n5. Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash\n\n## Questions\n\n### Which is better for AI agents, Azure OpenAI in Foundry Models or SiliconFlow?\n\nAzure OpenAI in Foundry Models scores 80 (A) on agent readiness against SiliconFlow's 42.9 (E), and leads in 6 of 7 scored categories. SiliconFlow leads on payments \u0026 pricing.\n\n### Do Azure OpenAI in Foundry Models and SiliconFlow need an API key?\n\nAzure OpenAI in Foundry Models takes an API key or an OAuth sign-in. SiliconFlow needs an API key.\n\n### Can an agent call Azure OpenAI in Foundry Models and SiliconFlow without installing anything?\n\nYes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and SiliconFlow at https://api.siliconflow.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-openai\", \"b\": \"siliconflow\"}`. From a terminal: `anchor compare azure-openai siliconflow`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-openai.json and https://www.anchorterminal.com/api/v1/tools/siliconflow.json\n\n## Other comparisons with Azure OpenAI in Foundry Models or SiliconFlow\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 SiliconFlow](https://www.anchorterminal.com/compare/amazon-bedrock-vs-siliconflow.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 SiliconFlow](https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs SiliconFlow](https://www.anchorterminal.com/compare/antseed-vs-siliconflow.md)\n- [Azure OpenAI in Foundry Models vs 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