{ "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 Beam 1.0's 53.4 (D), and leads in every scored category.", "b": { "slug": "reflection-beam", "name": "Beam 1.0", "vendor": "Reflection", "vendorUrl": "https://reflection.ai", "kind": "model", "category": "inference", "summary": "Beam 1.0 is Reflection's open-weight text model for coding, reasoning and agentic work, with 501B total and 23B active parameters and a 1M-token context, served by the Reflection API and released as Apache-2.0 weights.", "url": "https://www.anchorterminal.com/tools/reflection-beam", "markdownUrl": "https://www.anchorterminal.com/tools/reflection-beam.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/reflection-beam.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/reflection-beam.json", "dns": "reflection-beam.grade.anchorterminal.com", "repo": "https://huggingface.co/reflection/Beam-1.0-501B-A23B", "license": "Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service", "transports": [ "http" ], "remoteUrl": "https://api.reflection.ai/openai/v1", "packages": [], "auth": "api-key", "authNotes": "Bearer API key created by a person on platform.reflection.ai under API Keys. Each key belongs to one project and to the user who made it, is shown once, can be revoked from the API Keys page, and is disabled if that user leaves the organisation or project. No scopes, expiry or key-management API found. The docs say some organisations must verify a credit card in Billing before their keys work (`payment_method_required`). Self-hosted weights need no account; the Hugging Face repositories are not gated.", "pricing": "freemium", "pricingNotes": "No per-token or plan price for the Reflection API is published on a page we can read. The rate-limits docs describe a daily token allowance that renews at 00:00 UTC and ask those requesting higher limits whether they want paid usage, and some organisations must verify a credit card before keys work (https://developers.reflection.ai/rate-limits.md, checked 2026-11-04). Reflection's beta pricing page and terms are on reflection.ai, which disallows our crawler. The weights are free to self-host under Apache-2.0.", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Reflection docs, llms.txt or OpenAPI document. Access needs a browser sign-up on platform.reflection.ai and an API key (checked 2026-11-04).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-17" }, "docsUrl": "https://developers.reflection.ai/introduction", "rateLimitsUrl": "https://developers.reflection.ai/rate-limits", "llmsTxt": "https://developers.reflection.ai/llms.txt", "openapi": "https://developers.reflection.ai/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "self-hosted", "free", "openai-compatible", "openapi", "llms-txt", "status-page", "apache-2.0", "gpu", "new" ], "lastRelease": "2026-10-16", "graded": true, "anchor": { "graded": true, "score": 53.4, "grade": "D", "agentReady": false, "rank": 942, "ranked": true, "rankOf": 1486, "categoryRank": 31, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 67, "maintenance": 50, "payments": 10, "reliability": 52, "schema": 84, "security": 45, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-04" }, "negative": 0, "verdict": "The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026.", "bestFor": "An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.", "strengths": [ "OpenAI-compatible Chat Completions with `tool_choice`, parallel tool calls, strict tool schemas and `json_schema` structured outputs", "Error reference lists every status and code with whether to retry, and responses carry `Retry-After`, `x-should-retry` and `x-request-id`", "OpenAPI 3.0.3 document, llms.txt, a Markdown copy of every page and a docs MCP endpoint at developers.reflection.ai/mcp", "1,048,576-token context and up to 131,072 output tokens, with reasoning returned in its own `reasoning_content` field", "Weights in BF16, FP8 and NVFP4 under Apache-2.0, ungated, with Reflection's guides for SGLang, vLLM, TokenSpeed, Transformers, Helm and Dynamo" ], "weaknesses": [ "No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers", "Reasoning is mandatory and defaults to `max`, and a tool-call turn returned without `reasoning_content` makes every later request in that session fail", "No per-token price, retention period or subprocessor list on a page we can read; Reflection's terms and pricing pages are on a host that disallows our crawler", "Two API incidents labelled full outages on 14 and 15 October 2026 and three partial ones to 3 November", "No changelog and no model deprecation notice period found" ], "agentNotes": [ "Send `reasoning_effort` `low` or `medium` for short tasks. The default is `max`, and `none` or `minimal` return `400 unsupported_value`", "Return every assistant message with its `reasoning_content` unchanged. If a turn comes back without it, start a new conversation, since later requests fail with `missing_required_parameter`", "Don't rely on `stop` or `seed`. Both are accepted and ignored, so truncate output in your own code", "Honour `x-should-retry: false` on a 429. It means a daily limit is spent and `Retry-After` counts to 00:00 UTC", "Set `max_completion_tokens` yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.4 } ], "editorialScores": { "ergonomics": 67, "maintenance": 50, "payments": 10, "reliability": 52, "schema": 84, "security": 45, "transparency": 39 }, "provenanceScore": 74, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install openai # or: npm install openai, with base URL https://api.reflection.ai/openai/v1", "http": "curl https://api.reflection.ai/openai/v1/chat/completions \\\n -H \"Authorization: Bearer $REFLECTION_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"Beam-1.0-501B-A23B\",\n \"messages\": [\n {\"role\": \"user\", \"content\": \"Why is the sky blue?\"}\n ]\n }'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/reflection-beam" }, "sameCompany": [ "reflection-mirror" ], "area": "models", "provenance": { "legalEntity": "Reflection AI", "domain": "reflection.ai", "domainRegistered": "2017-12-16", "domainNote": "RDAP gave a registration date of 16 December 2017 and a transfer on 15 March 2024 on 17 October 2026 (not re-read; RDAP is a JSON service), so the domain predates the current owner.", "endpointOnVendorDomain": true, "terms": "https://reflection.ai/legal/commercial-terms-of-service", "privacy": "https://reflection.ai/legal/privacy-policy", "statusPage": "https://status.reflection.ai", "changelog": "", "securityTxt": "unknown", "checked": "2026-11-04", "notes": [ "reflection.ai's robots.txt disallows ClaudeBot, Claude-Web and anthropic-ai (read 4 November 2026), so the commercial terms, the privacy policy and reflection.ai's security.txt weren't re-read and their 17 October readings are struck. Both URLs are kept as listed facts.", "The legal entity is the copyright holder in the NOTICE files of Reflection's Mirror repository (`Copyright 2026 Reflection AI`), as on the reflection-mirror listing, since the fuller name came from struck pages.", "developers.reflection.ai/.well-known/security.txt returned 404 on 17 October 2026. The model card names reports@reflection.ai for security vulnerabilities.", "No changelog or release notes found in the developers docs or llms.txt (4 November 2026).", "status.reflection.ai answers robots.txt with a plain 404 (no rules) and was read under it." ], "score": 74 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/reflection-beam.json", "live": { "slug": "reflection-beam", "probe": { "target": "https://api.reflection.ai/openai/v1", "method": "get", "lastAt": "2026-11-07T18:20:50.527252886Z", "lastOk": true, "lastStatus": 404, "lastMs": 395, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 357, "p95ms24h": 478, "samples24h": 239, "samples30d": 5145, "days": [ { "date": "2026-10-17", "probes": 21, "ok": 21 }, { "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": 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 } ] }, "vendorStatus": { "page": "https://status.reflection.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T18:21:58.406534295Z" }, "securityTxt": { "url": "https://reflection.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:01.339118919Z" }, "llmsTxt": { "url": "https://developers.reflection.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:44.238449696Z" }, "domain": { "domain": "reflection.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/reflection.ai", "checkedAt": "2026-11-01T14:25:19.009468335Z" }, "pages": [ { "url": "https://reflection.ai/legal/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:18:16.340207649Z", "changedAt": "2026-11-07T14:18:16.340207649Z", "fingerprint": "10e2a9daf712" }, { "url": "https://reflection.ai/legal/commercial-terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:18:12.998666824Z", "changedAt": "2026-11-07T14:18:12.998666824Z", "fingerprint": "a3dff7b0d914" } ], "models": { "reflection/beam-1.0-501b-a23b": { "openrouterId": "reflection/beam-1.0-501b-a23b", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 131072, "checkedAt": "2026-11-03T23:49:21.261568406Z" } }, "updatedAt": "2026-11-07T18:21:58.406534295Z" } }, "edges": [ { "by": 50, "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. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training 10 of 20, partial kept. The API reference says each response's `reflection-data-retention` header reports `contributor` when content may be used to train Reflection's models \"under contributor terms your organization accepted\". The API safety page and commercial terms read on 17 October are struck (reflection.ai now disallows our crawler), so whether training is off by default can't be read. Retention 5 of 15, partial kept. The header can report `zero`, `standard` or `contributor`, and no readable page states periods or whether zero retention is offered. `x-request-id` on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). Security programme 5 of 20 (was 6). The model card names reports@reflection.ai for security vulnerabilities; developers.reflection.ai has no security.txt (404 on 17 October), and the safety report and reflection.ai's security.txt can't be read. No bug bounty, SOC 2 or ISO 27001 found on a readable page. 20 + 10 + 5 + 5 + 5 = 45." }, "scores": { "a": 95, "b": 45 } }, { "by": 36, "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. The weights were published on 16 October 2026, the date on the Hugging Face model page (the repository was created on 7 October); later commits to 30 October add evaluation results and a guide, which record no model change (30). One model, with a `shutdown_date` field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support through the platform and developers@reflection.ai for higher limits, and the model card names reports@reflection.ai. The Hub page shows 15 discussions (10 open, 5 closed), replies not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Reflection's serving guides for vLLM, SGLang, TokenSpeed, Transformers and Dynamo, a Beam Verifier repository, and fine-tuning recipes now published for NeMo AutoModel, Megatron Bridge, Axolotl and TRL (5 of 10, partial kept). 30 + 4 + 6 + 5 + 5 = 50." }, "scores": { "a": 86, "b": 50 } }, { "by": 31, "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 (tool use, structured output, caching, context, batch, SDKs and defaults, errors). `tool_choice` of auto, none, required or a named function, `parallel_tool_calls`, strict tools and up to 128 tools. The tool-calling loop needs `reasoning_content` sent back on every assistant turn, and the docs say the model sometimes returns a tool-call step without it, after which every request in the session fails (12 of 20). `json_object` and strict `json_schema` (15). Cached prompt tokens are reported in `usage`, but caching can't be steered, the `prompt_cache_*` options are ignored and no cached price exists in the beta (5 of 10). 1,048,576-token context and 131,072 output tokens (15). No batch endpoint (0 of 10). No Reflection SDK, the OpenAI Python and TypeScript SDKs are documented, and defaults cost an agent turns, with reasoning always on at `max`, `stop` and `seed` ignored and a default output budget not reduced to fit the prompt (5 of 10). Machine-readable `error.code` values with `param`, `x-should-retry`, `Retry-After` and `x-request-id` (15). 12 + 15 + 5 + 15 + 0 + 5 + 15 = 67, per the 17 October reading of the developers guides, not re-read on 4 November beyond the models and rate-limits pages." }, "scores": { "a": 98, "b": 67 } }, { "by": 28, "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": "Hosted lines, for the Reflection API. Status page at status.reflection.ai on incident.io, with API, platform and developer docs components and Atom and RSS feeds (20). In the 90 days to 4 November 2026 its incident pages list two full outages of the API component, a serving cluster down from 22:01 to 23:20 UTC on 14 October and elevated errors from 06:10 to 07:10 UTC on 15 October, each an hour or more, so two majors. Three more are labelled partial outages (16 October 02:28 to 02:38 UTC, 22 October rate-limit errors in two windows, 3 November about 20:10 to 21:38 UTC on one inference provider), read as minor. Two majors give 5. Rate limits are described per organisation in requests and tokens per minute and per day, with concurrency caps and headers, but no figures are published (5 of 15). 429 and 503 responses carry `Retry-After`, daily limits add `x-should-retry: false`, and the errors page says which codes to retry, with exponential backoff and jitter. There are no idempotency keys, and a chat completion is the billed call, so this run's value for retry guidance without idempotency keys gives 12 (was 15). No SLA found (0). The developers docs read on 4 November carry no beta or preview label for the API; the earlier beta reading came from reflection.ai pages now struck (10). 20 + 5 + 5 + 12 + 0 + 10 = 52." }, "scores": { "a": 80, "b": 52 } }, { "by": 26, "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": "Weights under Apache-2.0, an OSI licence, per the model card, which says the licence doesn't restrict distillation or training on outputs. The hosted API is a closed service whose commercial terms are on reflection.ai and can no longer be read (25 of 30, kept). Data handling 10 of 30, partial kept. What remains readable is the API reference's retention header (`zero`, `standard`, `contributor`) and the rate-limits page's request for data retention requirements; the terms, privacy policy, API safety page and zero-retention page are struck. Deprecation 4 of 20 (was 6). A `shutdown_date` field and a lifecycle section that says to move off a model before that date, with no notice period or dated notice; the fee-increase notice came from the struck terms. Subprocessors 0 of 20 (was 18). The list read on 17 October is on reflection.ai and struck, and no readable page names subprocessors or data locations. 25 + 10 + 4 + 0 = 39." }, "scores": { "a": 83, "b": 57 } }, { "by": 10, "category": "payments", "leads": "azure-openai", "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": "Graded on the Reflection API. No x402, MPP or L402 (0). No per-token, plan or allocation price is published on any readable page; the beta pricing page on reflection.ai is struck (0, was 10). Free tier 10 of 20, partial kept. The rate-limits page describes a daily token allowance and asks those requesting higher limits whether they are \"interested in paid usage\", and the authentication page says some organisations must verify a credit card before keys work. A person signs up in the browser at platform.reflection.ai to get a key (0). 0 + 0 + 10 + 0 = 10." }, "scores": { "a": 20, "b": 10 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Microsoft", "b": "Reflection", "name": "Vendor" }, { "a": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "b": "https://api.reflection.ai/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": "Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-26", "b": "2026-10-16", "name": "Last release" }, { "a": "no date given", "b": "2026-10-05", "name": "Terms last updated" }, { "a": "2026-09-01", "b": "2026-08-28", "name": "Privacy policy last updated" }, { "a": "yes", "b": "yes", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "454k npm/wk", "b": "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 Beam 1.0's 53.4 (D), and leads in every scored category.", "question": "Which is better for AI agents, Azure OpenAI in Foundry Models or Beam 1.0?" }, { "answer": "Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Beam 1.0 needs an API key.", "question": "Do Azure OpenAI in Foundry Models and Beam 1.0 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 Beam 1.0 at https://api.reflection.ai/openai/v1.", "question": "Can an agent call Azure OpenAI in Foundry Models and Beam 1.0 without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 80 against 52", "Agent ergonomics, 98 against 67", "Security \u0026 auth, 95 against 45", "Payments \u0026 pricing, 20 against 10", "Maintenance \u0026 community, 86 against 50", "Transparency \u0026 trust, 83 against 57" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Teams on Azure that need OpenAI models with Entra ID, private networking, EU or US data zones or FedRAMP scope, and one resource that also serves DeepSeek, Llama, Mistral and Grok models.", "slug": "azure-openai", "watchFor": "Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026" }, { "aheadOn": null, "also": null, "goodFor": "An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.", "slug": "reflection-beam", "watchFor": "No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers" } ], "history": { "azure-openai": null, "reflection-beam": [ { "causes": [ "evidence", "correction" ], "date": "2026-11-04", "delta": 0.1, "from": 53.3, "fromGrade": "D", "to": 53.4, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.1, "from": 53.4, "fromGrade": "D", "to": 53.3, "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": 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"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": 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"title": "Cerebras Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-reflection-beam.json", "title": "Cloudflare AI Gateway vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-reflection-beam.json", "title": "Cloudflare Workers AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam.json", "title": "Cohere Chat API (Command models) vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-reflection-beam.json", "title": "DeepInfra vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-reflection-beam.json", "title": "DeepSeek API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.json", "title": "Eden AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-reflection-beam.json", "title": "Glimpse vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam.json", "title": "Fireworks AI Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-reflection-beam.json", "title": "Gemini Developer API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-reflection-beam" }, { "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/hugging-face-inference-providers-vs-reflection-beam.json", "title": "Hugging Face Inference Providers vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam.json", "title": "Inkling 2 Small vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.json", "title": "Jais 3 vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.json", "title": "Meta Model API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam.json", "title": "MiniMax API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-reflection-beam.json", "title": "Mistral AI API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam.json", "title": "Muse Spark Open vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.json", "title": "Novita AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.json", "title": "OpenAI API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam.json", "title": "OpenRouter vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam.json", "title": "Prism Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam.json", "title": "Router.com (Ramp Router) vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus.json", "title": "Beam 1.0 vs RouterPlus", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova.json", "title": "Beam 1.0 vs SambaCloud", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova" }, { "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/reflection-beam-vs-simplismart.json", "title": "Beam 1.0 vs Simplismart", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.json", "title": "Beam 1.0 vs StepFun API", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash.json", "title": "Beam 1.0 vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub.json", "title": "Beam 1.0 vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.json", "title": "Beam 1.0 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway.json", "title": "Beam 1.0 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.json", "title": "Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.json", "title": "Beam 1.0 vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam.json", "title": "Nemotron 3.5 Super VL vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam" } ], "panel": null, "scores": [ { "azure-openai": 80, "by": 28, "edge": "azure-openai", "key": "reliability", "name": "Reliability", "reflection-beam": 52, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-openai": 87, "by": 3, "edge": "azure-openai", "key": "schema", "name": "Schema \u0026 documentation", "reflection-beam": 84, "weight": 13 }, { "azure-openai": 98, "by": 31, "edge": "azure-openai", "key": "ergonomics", "name": "Agent ergonomics", "reflection-beam": 67, "weight": 13 }, { "azure-openai": 95, "by": 50, "edge": "azure-openai", "key": "security", "name": "Security \u0026 auth", "reflection-beam": 45, "weight": 14 }, { "azure-openai": 20, "by": 10, "edge": "azure-openai", "key": "payments", "name": "Payments \u0026 pricing", "reflection-beam": 10, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-openai": 86, "by": 36, "edge": "azure-openai", "key": "maintenance", "name": "Maintenance \u0026 community", "reflection-beam": 50, "weight": 7 }, { "azure-openai": 83, "by": 26, "edge": "azure-openai", "key": "transparency", "name": "Transparency \u0026 trust", "reflection-beam": 57, "weight": 7 } ], "summary": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Beam 1.0's 53.4 (D), and leads in every scored category. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "azure-openai": "An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.", "reflection-beam": "The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam", "json": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.min.md" }, "markdown": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Beam 1.0's 53.4 (D), and leads in every scored category. 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- Beam 1.0: grade D, 53.4/100, rank #942 of 1486. Markdown https://www.anchorterminal.com/tools/reflection-beam.md · JSON https://www.anchorterminal.com/api/v1/tools/reflection-beam.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 52\n- Agent ergonomics, 98 against 67\n- Security \u0026 auth, 95 against 45\n- Payments \u0026 pricing, 20 against 10\n- Maintenance \u0026 community, 86 against 50\n- Transparency \u0026 trust, 83 against 57\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026\n\n### Beam 1.0 (D)\n\nGood for: An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.\n\nWatch for: No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers\n\n\n## Why the edge\n\n### Security \u0026 auth: Azure OpenAI in Foundry Models +50\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- Beam 1.0 (45): Model reading. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training 10 of 20, partial kept. The API reference says each response's `reflection-data-retention` header reports `contributor` when content may be used to train Reflection's models \"under contributor terms your organization accepted\". The API safety page and commercial terms read on 17 October are struck (reflection.ai now disallows our crawler), so whether training is off by default can't be read. Retention 5 of 15, partial kept. The header can report `zero`, `standard` or `contributor`, and no readable page states periods or whether zero retention is offered. `x-request-id` on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). Security programme 5 of 20 (was 6). The model card names reports@reflection.ai for security vulnerabilities; developers.reflection.ai has no security.txt (404 on 17 October), and the safety report and reflection.ai's security.txt can't be read. No bug bounty, SOC 2 or ISO 27001 found on a readable page. 20 + 10 + 5 + 5 + 5 = 45.\n\n### Maintenance \u0026 community: Azure OpenAI in Foundry Models +36\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- Beam 1.0 (50): Model reading. The weights were published on 16 October 2026, the date on the Hugging Face model page (the repository was created on 7 October); later commits to 30 October add evaluation results and a guide, which record no model change (30). One model, with a `shutdown_date` field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support through the platform and developers@reflection.ai for higher limits, and the model card names reports@reflection.ai. The Hub page shows 15 discussions (10 open, 5 closed), replies not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Reflection's serving guides for vLLM, SGLang, TokenSpeed, Transformers and Dynamo, a Beam Verifier repository, and fine-tuning recipes now published for NeMo AutoModel, Megatron Bridge, Axolotl and TRL (5 of 10, partial kept). 30 + 4 + 6 + 5 + 5 = 50.\n\n### Agent ergonomics: Azure OpenAI in Foundry Models +31\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- Beam 1.0 (67): Model reading (tool use, structured output, caching, context, batch, SDKs and defaults, errors). `tool_choice` of auto, none, required or a named function, `parallel_tool_calls`, strict tools and up to 128 tools. The tool-calling loop needs `reasoning_content` sent back on every assistant turn, and the docs say the model sometimes returns a tool-call step without it, after which every request in the session fails (12 of 20). `json_object` and strict `json_schema` (15). Cached prompt tokens are reported in `usage`, but caching can't be steered, the `prompt_cache_*` options are ignored and no cached price exists in the beta (5 of 10). 1,048,576-token context and 131,072 output tokens (15). No batch endpoint (0 of 10). No Reflection SDK, the OpenAI Python and TypeScript SDKs are documented, and defaults cost an agent turns, with reasoning always on at `max`, `stop` and `seed` ignored and a default output budget not reduced to fit the prompt (5 of 10). Machine-readable `error.code` values with `param`, `x-should-retry`, `Retry-After` and `x-request-id` (15). 12 + 15 + 5 + 15 + 0 + 5 + 15 = 67, per the 17 October reading of the developers guides, not re-read on 4 November beyond the models and rate-limits pages.\n\n### Reliability: Azure OpenAI in Foundry Models +28\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- Beam 1.0 (52): Hosted lines, for the Reflection API. Status page at status.reflection.ai on incident.io, with API, platform and developer docs components and Atom and RSS feeds (20). In the 90 days to 4 November 2026 its incident pages list two full outages of the API component, a serving cluster down from 22:01 to 23:20 UTC on 14 October and elevated errors from 06:10 to 07:10 UTC on 15 October, each an hour or more, so two majors. Three more are labelled partial outages (16 October 02:28 to 02:38 UTC, 22 October rate-limit errors in two windows, 3 November about 20:10 to 21:38 UTC on one inference provider), read as minor. Two majors give 5. Rate limits are described per organisation in requests and tokens per minute and per day, with concurrency caps and headers, but no figures are published (5 of 15). 429 and 503 responses carry `Retry-After`, daily limits add `x-should-retry: false`, and the errors page says which codes to retry, with exponential backoff and jitter. There are no idempotency keys, and a chat completion is the billed call, so this run's value for retry guidance without idempotency keys gives 12 (was 15). No SLA found (0). The developers docs read on 4 November carry no beta or preview label for the API; the earlier beta reading came from reflection.ai pages now struck (10). 20 + 5 + 5 + 12 + 0 + 10 = 52.\n\n### Transparency \u0026 trust: Azure OpenAI in Foundry Models +26\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- Beam 1.0 (57): Weights under Apache-2.0, an OSI licence, per the model card, which says the licence doesn't restrict distillation or training on outputs. The hosted API is a closed service whose commercial terms are on reflection.ai and can no longer be read (25 of 30, kept). Data handling 10 of 30, partial kept. What remains readable is the API reference's retention header (`zero`, `standard`, `contributor`) and the rate-limits page's request for data retention requirements; the terms, privacy policy, API safety page and zero-retention page are struck. Deprecation 4 of 20 (was 6). A `shutdown_date` field and a lifecycle section that says to move off a model before that date, with no notice period or dated notice; the fee-increase notice came from the struck terms. Subprocessors 0 of 20 (was 18). The list read on 17 October is on reflection.ai and struck, and no readable page names subprocessors or data locations. 25 + 10 + 4 + 0 = 39.\n\n### Payments \u0026 pricing: Azure OpenAI in Foundry Models +10\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- Beam 1.0 (10): Graded on the Reflection API. No x402, MPP or L402 (0). No per-token, plan or allocation price is published on any readable page; the beta pricing page on reflection.ai is struck (0, was 10). Free tier 10 of 20, partial kept. The rate-limits page describes a daily token allowance and asks those requesting higher limits whether they are \"interested in paid usage\", and the authentication page says some organisations must verify a credit card before keys work. A person signs up in the browser at platform.reflection.ai to get a key (0). 0 + 0 + 10 + 0 = 10.\n\n## Score by category\n\n| Category | Weight | Azure OpenAI in Foundry Models | Beam 1.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 52 | Azure OpenAI in Foundry Models +28 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 87 | 84 | Azure OpenAI in Foundry Models +3 |\n| Agent ergonomics | 13% (16.2 this run) | 98 | 67 | Azure OpenAI in Foundry Models +31 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 45 | Azure OpenAI in Foundry Models +50 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 10 | Azure OpenAI in Foundry Models +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 86 | 50 | Azure OpenAI in Foundry Models +36 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 83 | 57 | Azure OpenAI in Foundry Models +26 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **80 · A** | **53.4 · D** | |\n\n## Facts side by side\n\n| Fact | Azure OpenAI in Foundry Models | Beam 1.0 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Microsoft | Reflection |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | `https://api.reflection.ai/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 | Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-26 | 2026-10-16 |\n| Terms last updated | no date given | 2026-10-05 |\n| Privacy policy last updated | 2026-09-01 | 2026-08-28 |\n| Customer content may train models | yes | yes |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 454k npm/wk | none |\n| Agent reviews | none | 2.5/5 (4) |\n\n## How the scores have moved\n\n### Azure OpenAI in Foundry Models\n\nNo score change since it was listed.\n\n### Beam 1.0\n\n- +0.1 on 4 November 2026: new evidence, correction\n- -0.1 on 30 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**Beam 1.0.** The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026.\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### Beam 1.0\n\n1. Send `reasoning_effort` `low` or `medium` for short tasks. The default is `max`, and `none` or `minimal` return `400 unsupported_value`\n2. Return every assistant message with its `reasoning_content` unchanged. If a turn comes back without it, start a new conversation, since later requests fail with `missing_required_parameter`\n3. Don't rely on `stop` or `seed`. Both are accepted and ignored, so truncate output in your own code\n4. Honour `x-should-retry: false` on a 429. It means a daily limit is spent and `Retry-After` counts to 00:00 UTC\n5. Set `max_completion_tokens` yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens\n\n## Questions\n\n### Which is better for AI agents, Azure OpenAI in Foundry Models or Beam 1.0?\n\nAzure OpenAI in Foundry Models scores 80 (A) on agent readiness against Beam 1.0's 53.4 (D), and leads in every scored category.\n\n### Do Azure OpenAI in Foundry Models and Beam 1.0 need an API key?\n\nAzure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Beam 1.0 needs an API key.\n\n### Can an agent call Azure OpenAI in Foundry Models and Beam 1.0 without installing anything?\n\nYes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and Beam 1.0 at https://api.reflection.ai/openai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-openai\", \"b\": \"reflection-beam\"}`. From a terminal: `anchor compare azure-openai reflection-beam`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-openai.json and https://www.anchorterminal.com/api/v1/tools/reflection-beam.json\n\n## Other comparisons with Azure OpenAI in Foundry Models or Beam 1.0\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 Beam 1.0](https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam.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 Beam 1.0](https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs Beam 1.0](https://www.anchorterminal.com/compare/antseed-vs-reflection-beam.md)\n- [Azure OpenAI in Foundry Models 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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 GroqCloud](https://www.anchorterminal.com/compare/azure-openai-vs-groq.md)\n- [Azure OpenAI in Foundry Models vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.md)\n- [Azure OpenAI in Foundry Models vs Inkling 2 Small](https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small.md)\n- [Azure OpenAI in Foundry Models vs Jais 3](https://www.anchorterminal.com/compare/azure-openai-vs-jais-3.md)\n- [Azure OpenAI 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1.0](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-reflection-beam.md)\n- [Cloudflare Workers AI vs Beam 1.0](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-reflection-beam.md)\n- [Cohere Chat API (Command models) vs Beam 1.0](https://www.anchorterminal.com/compare/cohere-chat-vs-reflection-beam.md)\n- [DeepInfra vs Beam 1.0](https://www.anchorterminal.com/compare/deepinfra-vs-reflection-beam.md)\n- [DeepSeek API vs Beam 1.0](https://www.anchorterminal.com/compare/deepseek-api-vs-reflection-beam.md)\n- [Eden AI vs Beam 1.0](https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.md)\n- [Glimpse vs Beam 1.0](https://www.anchorterminal.com/compare/elorian-glimpse-vs-reflection-beam.md)\n- [Fireworks AI Inference vs Beam 1.0](https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam.md)\n- [Gemini Developer API vs Beam 1.0](https://www.anchorterminal.com/compare/gemini-api-vs-reflection-beam.md)\n- [GroqCloud vs Beam 1.0](https://www.anchorterminal.com/compare/groq-vs-reflection-beam.md)\n- [Hugging Face Inference Providers vs Beam 1.0](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.md)\n- [Inkling 2 Small vs Beam 1.0](https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam.md)\n- [Jais 3 vs Beam 1.0](https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.md)\n- [Meta Model API vs Beam 1.0](https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.md)\n- [MiniMax API vs Beam 1.0](https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam.md)\n- [Mistral AI API vs Beam 1.0](https://www.anchorterminal.com/compare/mistral-api-vs-reflection-beam.md)\n- [Muse Spark Open vs Beam 1.0](https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam.md)\n- [Novita AI vs Beam 1.0](https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.md)\n- [OpenAI API vs Beam 1.0](https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.md)\n- [OpenRouter vs Beam 1.0](https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam.md)\n- [Prism Inference vs Beam 1.0](https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam.md)\n- [Router.com (Ramp Router) vs Beam 1.0](https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam.md)\n- [Beam 1.0 vs RouterPlus](https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus.md)\n- [Beam 1.0 vs SambaCloud](https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova.md)\n- [Beam 1.0 vs SiliconFlow](https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.md)\n- [Beam 1.0 vs Simplismart](https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart.md)\n- [Beam 1.0 vs StepFun API](https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.md)\n- [Beam 1.0 vs SWE-2 Flash](https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash.md)\n- [Beam 1.0 vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub.md)\n- [Beam 1.0 vs Together AI Inference](https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.md)\n- [Beam 1.0 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway.md)\n- [Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.md)\n- [Beam 1.0 vs xAI API (Grok)](https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs Beam 1.0](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam.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 Beam 1.0", "url": "" } ], "description": "Azure OpenAI in Foundry Models scores 80 (A) to Beam 1.0's 53.4 (D) for llm inference. 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