{ "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 Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on schema \u0026 documentation.", "b": { "slug": "together-inference", "name": "Together AI Inference", "vendor": "Together Computer, Inc.", "vendorUrl": "https://www.together.ai", "kind": "http-api", "category": "inference", "summary": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput. Model-dependent capabilities include tool calling, structured outputs and vision.", "url": "https://www.anchorterminal.com/tools/together-inference", "markdownUrl": "https://www.anchorterminal.com/tools/together-inference.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/together-inference.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/together-inference.json", "dns": "together-inference.grade.anchorterminal.com", "repo": "https://github.com/togethercomputer/together-py", "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.together.ai/v1", "packages": [ { "registry": "pypi", "name": "together", "main": true }, { "registry": "npm", "name": "together-ai", "main": true } ], "auth": "api-key", "authNotes": "Bearer API keys are scoped to projects, can expire and can be revoked separately. A key has full access to resources in its project. There are no per-key spending or rate limits; legacy default-project keys should be replaced.", "pricing": "paid", "pricingNotes": "Prepaid usage with a $15 minimum first credit purchase, then $5 minimum top-ups. No free trial. GPT OSS 120B is $0.15 per million input tokens and $0.60 per million output tokens. Dedicated hardware and provisioned throughput have separate rates.", "priceSummary": "Paid", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 10, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://docs.together.ai", "llmsTxt": "https://docs.together.ai/llms.txt", "openapi": "https://docs.together.ai/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "http-api", "inference", "api-key", "openapi", "llms-txt", "paid" ], "lastRelease": "2026-10-23", "graded": true, "anchor": { "graded": true, "score": 67.8, "grade": "B", "agentReady": false, "rank": 301, "ranked": true, "rankOf": 1486, "categoryRank": 13, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 75, "schema": 93, "security": 70, "transparency": 74 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -3, "negativeNotes": [ "2026-08-19 to 2026-08-27. Together removed GA serverless models with notice posted only on the day of removal. Changelog entries of 19, 21, 25 and 27 August say FLUX.1 schnell, Qwen2.5 7B, Kimi K2.6, Cogito v2.1 671B, Gemma 3n E4B, Llama Guard 4 12B, Nemotron 3 Ultra, Pearl's Gemma 4 31B, DeepSeek V4 Pro and Kimi K2.7 Code \"have been deprecated and are no longer available on serverless\", with no earlier entry announcing their removal and no preview label, while the deprecation policy promises 2 or 3 weeks' notice for serverless endpoints. Read at the floor, as fireworks-inference's same-day removals of 27 August were, -3 (https://docs.together.ai/docs/changelog.md)." ], "verdict": "A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted.", "bestFor": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.", "strengths": [ "Public OpenAPI 3.1, Markdown documentation and Python and TypeScript SDKs", "Project-scoped API keys with optional expiry and per-key cost attribution", "Serverless, batch, dedicated and provisioned-throughput options", "Status page with a monitor per serverless model and 90 days of daily history", "US-only serverless processing through us-api.together.ai since 16 October 2026, at 1.25 times standard rates" ], "weaknesses": [ "A $15 credit purchase is required before platform access; no free trial", "Prompt and response storage is on by default; zero data retention must be enabled for the organisation", "Serverless has no guaranteed capacity outside provisioned throughput, and API keys have no individual spend caps", "Serverless models removed on 19, 21, 25 and 27 August 2026 were announced in the changelog only on the day" ], "agentNotes": [ "Create a project-scoped key and set TOGETHER_API_KEY. Avoid deprecated legacy keys.", "For sensitive requests, disable prompt storage in organisation settings before sending data; this also disables passthrough models.", "Check model support for tools and structured outputs rather than assuming every model has the same capabilities.", "Back off on 429 and 503 responses. Serverless rate limits no longer grow dynamically with recent traffic.", "Check the deprecation schedule before choosing a model. Qwen3.8-2.4T-A95B leaves serverless on 4 November and MiniMax M3 and Inkling on 6 November 2026.", "Pin the SDK major version. Python SDK 3.0 and TypeScript SDK 1.0 (22 October 2026) drop `/v1` from the base URL and the `beta` paths" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.8 } ], "editorialScores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 75, "schema": 93, "security": 70, "transparency": 65 }, "provenanceScore": 83, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl 'https://api.together.ai/v1/chat/completions' -H \"Authorization: Bearer $TOGETHER_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"openai/gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/together-inference" }, "sameCompany": [ "together-fine-tuning", "together-gpu-clusters", "together-code-sandbox" ], "area": "models", "unitPrices": [ { "item": "GPT OSS 120B input", "unit": "1m-tokens", "usd": 0.15, "note": "Shared/serverless standard rate, per million tokens, checked 1 November 2026" }, { "item": "GPT OSS 120B output", "unit": "1m-tokens", "usd": 0.6, "note": "Shared/serverless standard rate, per million tokens, checked 1 November 2026" } ], "provenance": { "legalEntity": "Together Computer, Inc.", "domain": "together.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://www.together.ai/terms-of-service", "privacy": "https://www.together.ai/privacy", "statusPage": "https://status.together.ai", "changelog": "https://docs.together.ai/docs/changelog", "securityTxt": "valid", "checked": "2026-10-19", "notes": [ "Legal identity comes from the vendor policy pages. Domain registration was not checked.", "The SDK repository is not the source for the hosted inference service.", "security.txt names the HackerOne programme and expires on 30 September 2028." ], "score": 83 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/together-inference.json", "live": { "slug": "together-inference", "probe": { "target": "https://api.together.ai/v1", "method": "get", "lastAt": "2026-11-07T18:21:01.011134739Z", "lastOk": true, "lastStatus": 404, "lastMs": 210, "authRequired": false, "uptime24h": 100, "uptime30d": 99.98, "p50ms24h": 200, "p95ms24h": 488, "samples24h": 239, "samples30d": 4786, "days": [ { "date": "2026-10-19", "probes": 173, "ok": 173 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 250, "ok": 249 }, { "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.together.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-03T15:50:27.832032204Z" }, "versions": [ { "registry": "github", "name": "togethercomputer/together-py", "version": "v3.1.1", "released": "2026-11-04", "seenAt": "2026-11-07T00:12:19.125880583Z" }, { "registry": "npm", "name": "together-ai", "version": "1.0.0", "seenAt": "2026-11-07T00:12:19.091822114Z" }, { "registry": "pypi", "name": "together", "version": "3.1.1", "released": "2026-11-04", "seenAt": "2026-11-07T00:12:18.875614418Z" } ], "githubStars": 12, "npmWeekly": 99619, "pypiWeekly": 424792, "securityTxt": { "url": "https://together.ai/.well-known/security.txt", "state": "valid", "expires": "2028-09-30T00:00:00.000Z", "checkedAt": "2026-11-07T16:00:47.073630606Z" }, "llmsTxt": { "url": "https://docs.together.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:34:14.123755248Z" }, "domain": { "domain": "together.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/together.ai", "checkedAt": "2026-11-01T14:21:27.260418255Z" }, "github": { "repo": "togethercomputer/together-py", "checkedAt": "2026-11-02T08:27:14.179460754Z", "stars": 11, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T05:50:24Z", "openIssues": 4, "openPRs": 43, "issuesOpened90d": 2, "issuesClosed90d": 1, "prsMerged90d": 106, "ci": { "branch": "main", "runs": 50, "success": 16, "failure": 0, "other": 34, "latest": "skipped", "latestAt": "2026-10-30T19:38:40Z" }, "replies": { "sampled": 7, "unanswered": 4, "medianDays": 14.2 } }, "updatedAt": "2026-11-07T18:21:01.011134739Z" } }, "edges": [ { "by": 25, "category": "security", "leads": "azure-openai", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. Microsoft Entra ID tokens with Azure roles (the Cognitive Services OpenAI User role for calls), managed identities, and key authentication that can be disabled per resource, or two regenerable resource keys in the `api-key` header. No documented route puts the key in a URL query string (30). Prompts, completions, embeddings and training data aren't used to train foundation models without the customer's permission or instruction, per the data privacy page updated 4 August 2026 (20). Flagged prompts and completions may be stored in the customer's geography for human abuse review, with no retention period stated, and approved customers can turn that storage off through modified abuse monitoring. Responses API data is kept 30 days by default unless `store` is false (12 of 15). Azure Monitor resource logs and the subscription activity log, as read in the Foundry fine-tuning dossier (15). MSRC coordinated disclosure policy and Microsoft's bounty programme, both named in microsoft.com's security.txt, and Azure OpenAI is listed in FedRAMP High and DoD IL2 scope in Azure public regions. The security.txt passed its Expires date on 2026-09-23 and was still expired on 6 November, which the Bedrock and S3 dossiers mark down by 2, applied here too (18 of 20, down from 20 on 6 October for consistency).", "b": "Project-scoped, revocable keys with optional expiry and rotation guidance (30). Project boundaries but keys can access all project resources and lack per-key spend limits (10 of 20). No inference prompt-injection mitigation established (0). Per-key cost and usage attribution (15). Published security.txt with a future expiry and HackerOne disclosure route (15 of 20)." }, "scores": { "a": 95, "b": 70 } }, { "by": 21, "category": "maintenance", "leads": "azure-openai", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. GPT-6.1 Terra released on Azure on 26 October 2026 and a `gpt-chat-latest` preview of 7 October was added, after GPT-6.1 Sol on 29 September (30). GA models get a retirement date 18 months after launch, set at release and readable through the Models API, with at least 60 days' email and Service Health notice, and previews at least 30 days, so a GA retirement is known more than six months ahead (12 of 12). Many shutdown dates in the 90 days to 6 November, most of them previews or partner models, among them DeepSeek-R1 (13 August), MAI-Image-2 and 2e (15 August), model-router previews (30 August), MAI-Transcribe-1 (15 September), MAI-Image-2.5 previews (1 October), the 2025-03-20 audio models and sora-2 (15 October), a Cohere Command A Plus preview (16 October) and gpt-image-1 (23 October), each in the schedule with a replacement where one exists (4 of 8). The Foundry what's new page, still on August when read on 6 November, plus Microsoft Q\u0026A and paid support; no Azure OpenAI what's new was found (10 of 15). The SDKs are OpenAI's repositories, replies not sampled (5 of 10). Current official SDKs, `openai` 3.46.0 on PyPI (5 November) and 7.53.0 on npm, plus Microsoft's `@azure/openai` 2.0.0 companion (15). Supported runtimes stated, Python 3.9 or later and Node.js 20 or later, though `openai` 3.46.0 requires Python 3.10 (10).", "b": "Graded as listed, on the tool lines. Changelog entries on 22 and 23 October 2026 (Python SDK 3.0, TypeScript SDK 1.0, MiniMax M3.1 Flash on serverless and post-training) (30). 43 dated changelog days and 16 Python SDK tags from 3 August, v2.33.1 to v3.0.0 (20). Support responsiveness not tested (0). Official Python and TypeScript SDKs, both given new majors on 22 October (15). Dependency and CI health not audited (0)." }, "scores": { "a": 86, "b": 65 } }, { "by": 13, "category": "ergonomics", "leads": "azure-openai", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and a forced call by naming the function in `tool_choice`, 18 of 20 because `gpt-6.1-sol` calls tools only through the Responses API (18). Strict structured outputs (15). Prompt caching from 1,024 tokens, cached input at 0.1x on GPT-6 ($1 per million on Astra) and cache writes at 1.25x from GPT-5.6 on, with explicit breakpoints (15). 1,050,000-token context on GPT-6 and GPT-6.1, input capped at 922,000 (15). Batch at 50% off Global Standard with a 24-hour target (10). The docs use OpenAI's own SDKs for Python, JavaScript, C#, Go and Java against the v1 endpoint (10). 429 and quota errors documented with retry headers (15). Calls name a deployment rather than a model, so each model must be deployed in the resource first, which the model checklist doesn't score.", "b": "Compact model API with bounded output (25). Token controls, streaming, structured outputs and batch options (20). Actionable error documentation (20). Transient retry guidance but no general inference deduplication guarantee found (5 of 20). Official Python and TypeScript SDKs and defaults (15)." }, "scores": { "a": 98, "b": 85 } }, { "by": 9, "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": "Proprietary service with published terms and Apache-2.0 SDK (15). Docs distinguish default content storage, training opt-in, organisation ZDR and passthrough models, but default content retention has no fixed duration in the reviewed pages (25 of 30). Public lifecycle policy gives a two-week migration window for breaking model upgrades and 2 or 3 weeks' notice for serverless removals, though removals on 19, 21, 25 and 27 August 2026 were posted only on the day (15 of 20). North American hosting and enterprise residency options are described; full subprocessor locations were not established (10 of 20)." }, "scores": { "a": 83, "b": 74 } }, { "by": 6, "category": "schema", "leads": "together-inference", "name": "Schema \u0026 documentation", "reasons": { "a": "OpenAPI 3.2 spec for the v1 data plane in Azure/azure-rest-api-specs (`azure-v1-v1-generated.json`, 71 paths and 852 schemas), linked from the v1 API page (25). No llms.txt at learn.microsoft.com (404). Learn pages offer Copy Markdown and the Markdown sources are public in MicrosoftDocs/azure-ai-docs, last merged 5 October (5 of 10). The models page lists each model's capabilities, context and API support, but the model choice guide, dated 19 May 2026, doesn't cover GPT-6 (15 of 20). Structured outputs with `strict: true` on schemas and function tools, though not together with parallel function calls (15). Examples in Python, C#, JavaScript, Go, Java and REST, and an error table on the quotas page with a fix for 429 and other codes (15). The v1 path replaces monthly `api-version` values, with preview capabilities opted into by header, a dated API version changelog and dated model versions. On 6 November the Foundry what's new still covered August, though updated on 5 November, and no Azure OpenAI what's new was found at learn.microsoft.com/en-us/azure/foundry/openai/whats-new, which answered 404 (12 of 15).", "b": "Public OpenAPI 3.1 (25), llms.txt and Markdown docs (10), endpoint and model-capability guidance (16 of 20), typed inputs and constraints (13 of 15), examples and documented errors (14 of 15), and versioned endpoints with a dated changelog (15)." }, "scores": { "a": 87, "b": 93 } }, { "by": 5, "category": "reliability", "leads": "azure-openai", "name": "Reliability", "reasons": { "a": "Azure status page with post-incident reviews, listing Azure OpenAI Service, Foundry Models and Foundry Agent Service as components (20). One incident in the 90 days to 6 November 2026 names Azure OpenAI, and no review after it does, intermittent request failures, higher latency and HTTP 5xx errors in Sweden Central from 10:03 to 15:58 UTC on 29 September 2026 (tracking 7QL5-Z50), counted as one major outage as in the Foundry fine-tuning dossier. The 23 July West US review and the 30 September gateway incident don't name it (10). Quota tiers from Free to Tier 6 with TPM and RPM per model and deployment type, 1,000 RPM and 1,000,000 TPM for each GPT-6 model on Global Standard at Tier 1 (15). 429 responses carry `retry-after-ms`, every response carries `x-ratelimit-*` headers, and the quota guide gives exponential backoff with jitter and SDK retry settings (15). The models page says models sold by Azure are covered by Azure service-level agreements and links the Online Services SLA. The consolidated SLA document wouldn't download on 6 October and wasn't retried on 6 November, so the clause rests on Microsoft's docs, read the same way as the 5 October Azure Speech check (10). The v1 API is GA and the GPT-6 models carry no preview label (10).", "b": "Graded as listed, on the hosted API lines. Public Better Stack status page at status.together.ai with a component for each serverless model plus the website and playground (20). The page shows 90 daily ticks per component, read on 1 November 2026 for 4 August to 1 November, and no incident was posted in that time (the feed's newest items are maintenance windows in April and July 2026). Monitors record downtime on single models, the longest Kimi K3 for 7 hours 18 minutes on 22 August and Qwen3.8-2.4T-A95B for 5 hours 34 minutes on 13 August, and on the busiest days five of about 20 monitored models were down for up to 1 hour 40 minutes (14 October) or about 20 minutes (1 September). Each hit one model or a subset of the catalogue, so the record reads as minor incidents only (20). The current serverless page gives no numeric general request ceiling (0). Explicit 429 and 503 backoff guidance (15). Provisioned throughput has a published 99% eligible-request commitment (10). Serverless inference is generally available (10). 20 + 20 + 0 + 15 + 10 + 10 = 75." }, "scores": { "a": 80, "b": 75 } } ], "facts": [ { "a": "Model API", "b": "HTTP API", "name": "Kind" }, { "a": "Microsoft", "b": "Together Computer, Inc.", "name": "Vendor" }, { "a": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "b": "https://api.together.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Paid", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the Microsoft Product Terms. The v1 OpenAPI spec is MIT, and the OpenAI SDKs the docs use are Apache-2.0", "b": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-26", "b": "2026-10-23", "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": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "454k npm/wk", "b": "10 stars", "name": "Popularity" }, { "a": "none", "b": "3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on schema \u0026 documentation.", "question": "Which is better for AI agents, Azure OpenAI in Foundry Models or Together AI Inference?" }, { "answer": "Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Together AI Inference needs an API key.", "question": "Do Azure OpenAI in Foundry Models and Together AI Inference need an API key?" }, { "answer": "Yes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and Together AI Inference at https://api.together.ai/v1.", "question": "Can an agent call Azure OpenAI in Foundry Models and Together AI Inference without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 80 against 75", "Agent ergonomics, 98 against 85", "Security \u0026 auth, 95 against 70", "Maintenance \u0026 community, 86 against 65", "Transparency \u0026 trust, 83 against 74" ], "also": [ "Agent-ready, a grade of BB or better", "No incidents deducted, where Together AI Inference 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": [ "Schema \u0026 documentation, 93 against 87" ], "also": null, "goodFor": "Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.", "slug": "together-inference", "watchFor": "A $15 credit purchase is required before platform access; no free trial" } ], "history": { "azure-openai": null, "together-inference": [ { "causes": [ "evidence", "correction" ], "date": "2026-11-01", "delta": 0, "from": 67.8, "fromGrade": "B", "to": 67.8, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0, "from": 67.8, "fromGrade": "B", "to": 67.8, "toGrade": "B" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.json", "title": "Amazon Bedrock vs Azure OpenAI in Foundry Models", "url": 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"url": "https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-together-inference.json", "title": "DeepInfra vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-together-inference.json", "title": "DeepSeek API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.json", "title": "Eden AI vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-together-inference.json", "title": "Glimpse vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference.json", "title": "Fireworks AI Inference vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-together-inference.json", "title": "Gemini Developer API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-together-inference.json", "title": "GroqCloud vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/groq-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference.json", "title": "Hugging Face Inference Providers vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-together-inference.json", "title": "Inkling 2 Small vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-together-inference.json", "title": "Jais 3 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/jais-3-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.json", "title": "Meta Model API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-together-inference.json", "title": "MiniMax API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-together-inference.json", "title": "Mistral AI API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.json", "title": "Muse Spark Open vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-together-inference.json", "title": "Novita AI vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference.json", "title": "OpenAI API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-together-inference.json", "title": "OpenRouter vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/openrouter-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-together-inference.json", "title": "Prism Inference vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-together-inference.json", "title": "Router.com (Ramp Router) vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-together-inference" }, { "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/routerplus-vs-together-inference.json", "title": "RouterPlus vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/routerplus-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-together-inference.json", "title": "SambaCloud vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/sambanova-vs-together-inference" }, { "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/simplismart-vs-together-inference.json", "title": "Simplismart vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/simplismart-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference.json", "title": "StepFun API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-together-inference.json", "title": "SWE-2 Flash vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference.json", "title": "Tencent Cloud TokenHub vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway.json", "title": "Together AI Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.json", "title": "Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api.json", "title": "Together AI Inference vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-together-inference.json", "title": "Nemotron 3.5 Super VL vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-together-inference" } ], "panel": null, "scores": [ { "azure-openai": 80, "by": 5, "edge": "azure-openai", "key": "reliability", "name": "Reliability", "together-inference": 75, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-openai": 87, "by": 6, "edge": "together-inference", "key": "schema", "name": "Schema \u0026 documentation", "together-inference": 93, "weight": 13 }, { "azure-openai": 98, "by": 13, "edge": "azure-openai", "key": "ergonomics", "name": "Agent ergonomics", "together-inference": 85, "weight": 13 }, { "azure-openai": 95, "by": 25, "edge": "azure-openai", "key": "security", "name": "Security \u0026 auth", "together-inference": 70, "weight": 14 }, { "azure-openai": 20, "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "together-inference": 20, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-openai": 86, "by": 21, "edge": "azure-openai", "key": "maintenance", "name": "Maintenance \u0026 community", "together-inference": 65, "weight": 7 }, { "azure-openai": 83, "by": 9, "edge": "azure-openai", "key": "transparency", "name": "Transparency \u0026 trust", "together-inference": 74, "weight": 7 } ], "summary": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on schema \u0026 documentation. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "azure-openai": "An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.", "together-inference": "A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference", "json": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.min.md" }, "markdown": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on schema \u0026 documentation. Both do llm inference.\n\n- Azure OpenAI in Foundry Models: grade A, 80/100, rank #14 of 1486. Markdown https://www.anchorterminal.com/tools/azure-openai.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-openai.json\n- Together AI Inference: grade B, 67.8/100, rank #301 of 1486. Markdown https://www.anchorterminal.com/tools/together-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/together-inference.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Azure OpenAI in Foundry Models (A)\n\nGood for: Teams on Azure that need OpenAI models with Entra ID, private networking, EU or US data zones or FedRAMP scope, and one resource that also serves DeepSeek, Llama, Mistral and Grok models.\n\nAhead on:\n- Reliability, 80 against 75\n- Agent ergonomics, 98 against 85\n- Security \u0026 auth, 95 against 70\n- Maintenance \u0026 community, 86 against 65\n- Transparency \u0026 trust, 83 against 74\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- No incidents deducted, where Together AI Inference 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### Together AI Inference (B)\n\nGood for: Together AI Inference serves open models through an OpenAI-compatible API, with serverless requests, batch processing, dedicated model deployments and provisioned throughput.\n\nAhead on:\n- Schema \u0026 documentation, 93 against 87\n\nWatch for: A $15 credit purchase is required before platform access; no free trial\n\n\n## Why the edge\n\n### Security \u0026 auth: Azure OpenAI in Foundry Models +25\n\n- Azure OpenAI in Foundry Models (95): Model reading. Microsoft Entra ID tokens with Azure roles (the Cognitive Services OpenAI User role for calls), managed identities, and key authentication that can be disabled per resource, or two regenerable resource keys in the `api-key` header. No documented route puts the key in a URL query string (30). Prompts, completions, embeddings and training data aren't used to train foundation models without the customer's permission or instruction, per the data privacy page updated 4 August 2026 (20). Flagged prompts and completions may be stored in the customer's geography for human abuse review, with no retention period stated, and approved customers can turn that storage off through modified abuse monitoring. Responses API data is kept 30 days by default unless `store` is false (12 of 15). Azure Monitor resource logs and the subscription activity log, as read in the Foundry fine-tuning dossier (15). MSRC coordinated disclosure policy and Microsoft's bounty programme, both named in microsoft.com's security.txt, and Azure OpenAI is listed in FedRAMP High and DoD IL2 scope in Azure public regions. The security.txt passed its Expires date on 2026-09-23 and was still expired on 6 November, which the Bedrock and S3 dossiers mark down by 2, applied here too (18 of 20, down from 20 on 6 October for consistency).\n- Together AI Inference (70): Project-scoped, revocable keys with optional expiry and rotation guidance (30). Project boundaries but keys can access all project resources and lack per-key spend limits (10 of 20). No inference prompt-injection mitigation established (0). Per-key cost and usage attribution (15). Published security.txt with a future expiry and HackerOne disclosure route (15 of 20).\n\n### Maintenance \u0026 community: Azure OpenAI in Foundry Models +21\n\n- Azure OpenAI in Foundry Models (86): Model reading. GPT-6.1 Terra released on Azure on 26 October 2026 and a `gpt-chat-latest` preview of 7 October was added, after GPT-6.1 Sol on 29 September (30). GA models get a retirement date 18 months after launch, set at release and readable through the Models API, with at least 60 days' email and Service Health notice, and previews at least 30 days, so a GA retirement is known more than six months ahead (12 of 12). Many shutdown dates in the 90 days to 6 November, most of them previews or partner models, among them DeepSeek-R1 (13 August), MAI-Image-2 and 2e (15 August), model-router previews (30 August), MAI-Transcribe-1 (15 September), MAI-Image-2.5 previews (1 October), the 2025-03-20 audio models and sora-2 (15 October), a Cohere Command A Plus preview (16 October) and gpt-image-1 (23 October), each in the schedule with a replacement where one exists (4 of 8). The Foundry what's new page, still on August when read on 6 November, plus Microsoft Q\u0026A and paid support; no Azure OpenAI what's new was found (10 of 15). The SDKs are OpenAI's repositories, replies not sampled (5 of 10). Current official SDKs, `openai` 3.46.0 on PyPI (5 November) and 7.53.0 on npm, plus Microsoft's `@azure/openai` 2.0.0 companion (15). Supported runtimes stated, Python 3.9 or later and Node.js 20 or later, though `openai` 3.46.0 requires Python 3.10 (10).\n- Together AI Inference (65): Graded as listed, on the tool lines. Changelog entries on 22 and 23 October 2026 (Python SDK 3.0, TypeScript SDK 1.0, MiniMax M3.1 Flash on serverless and post-training) (30). 43 dated changelog days and 16 Python SDK tags from 3 August, v2.33.1 to v3.0.0 (20). Support responsiveness not tested (0). Official Python and TypeScript SDKs, both given new majors on 22 October (15). Dependency and CI health not audited (0).\n\n### Agent ergonomics: Azure OpenAI in Foundry Models +13\n\n- Azure OpenAI in Foundry Models (98): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and a forced call by naming the function in `tool_choice`, 18 of 20 because `gpt-6.1-sol` calls tools only through the Responses API (18). Strict structured outputs (15). Prompt caching from 1,024 tokens, cached input at 0.1x on GPT-6 ($1 per million on Astra) and cache writes at 1.25x from GPT-5.6 on, with explicit breakpoints (15). 1,050,000-token context on GPT-6 and GPT-6.1, input capped at 922,000 (15). Batch at 50% off Global Standard with a 24-hour target (10). The docs use OpenAI's own SDKs for Python, JavaScript, C#, Go and Java against the v1 endpoint (10). 429 and quota errors documented with retry headers (15). Calls name a deployment rather than a model, so each model must be deployed in the resource first, which the model checklist doesn't score.\n- Together AI Inference (85): Compact model API with bounded output (25). Token controls, streaming, structured outputs and batch options (20). Actionable error documentation (20). Transient retry guidance but no general inference deduplication guarantee found (5 of 20). Official Python and TypeScript SDKs and defaults (15).\n\n### Transparency \u0026 trust: Azure OpenAI in Foundry Models +9\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- Together AI Inference (74): Proprietary service with published terms and Apache-2.0 SDK (15). Docs distinguish default content storage, training opt-in, organisation ZDR and passthrough models, but default content retention has no fixed duration in the reviewed pages (25 of 30). Public lifecycle policy gives a two-week migration window for breaking model upgrades and 2 or 3 weeks' notice for serverless removals, though removals on 19, 21, 25 and 27 August 2026 were posted only on the day (15 of 20). North American hosting and enterprise residency options are described; full subprocessor locations were not established (10 of 20).\n\n### Schema \u0026 documentation: Together AI Inference +6\n\n- Azure OpenAI in Foundry Models (87): OpenAPI 3.2 spec for the v1 data plane in Azure/azure-rest-api-specs (`azure-v1-v1-generated.json`, 71 paths and 852 schemas), linked from the v1 API page (25). No llms.txt at learn.microsoft.com (404). Learn pages offer Copy Markdown and the Markdown sources are public in MicrosoftDocs/azure-ai-docs, last merged 5 October (5 of 10). The models page lists each model's capabilities, context and API support, but the model choice guide, dated 19 May 2026, doesn't cover GPT-6 (15 of 20). Structured outputs with `strict: true` on schemas and function tools, though not together with parallel function calls (15). Examples in Python, C#, JavaScript, Go, Java and REST, and an error table on the quotas page with a fix for 429 and other codes (15). The v1 path replaces monthly `api-version` values, with preview capabilities opted into by header, a dated API version changelog and dated model versions. On 6 November the Foundry what's new still covered August, though updated on 5 November, and no Azure OpenAI what's new was found at learn.microsoft.com/en-us/azure/foundry/openai/whats-new, which answered 404 (12 of 15).\n- Together AI Inference (93): Public OpenAPI 3.1 (25), llms.txt and Markdown docs (10), endpoint and model-capability guidance (16 of 20), typed inputs and constraints (13 of 15), examples and documented errors (14 of 15), and versioned endpoints with a dated changelog (15).\n\n### Reliability: Azure OpenAI in Foundry Models +5\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- Together AI Inference (75): Graded as listed, on the hosted API lines. Public Better Stack status page at status.together.ai with a component for each serverless model plus the website and playground (20). The page shows 90 daily ticks per component, read on 1 November 2026 for 4 August to 1 November, and no incident was posted in that time (the feed's newest items are maintenance windows in April and July 2026). Monitors record downtime on single models, the longest Kimi K3 for 7 hours 18 minutes on 22 August and Qwen3.8-2.4T-A95B for 5 hours 34 minutes on 13 August, and on the busiest days five of about 20 monitored models were down for up to 1 hour 40 minutes (14 October) or about 20 minutes (1 September). Each hit one model or a subset of the catalogue, so the record reads as minor incidents only (20). The current serverless page gives no numeric general request ceiling (0). Explicit 429 and 503 backoff guidance (15). Provisioned throughput has a published 99% eligible-request commitment (10). Serverless inference is generally available (10). 20 + 20 + 0 + 15 + 10 + 10 = 75.\n\n## Score by category\n\n| Category | Weight | Azure OpenAI in Foundry Models | Together AI Inference | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 75 | Azure OpenAI in Foundry Models +5 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 87 | 93 | Together AI Inference +6 |\n| Agent ergonomics | 13% (16.2 this run) | 98 | 85 | Azure OpenAI in Foundry Models +13 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 70 | Azure OpenAI in Foundry Models +25 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 86 | 65 | Azure OpenAI in Foundry Models +21 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 83 | 74 | Azure OpenAI in Foundry Models +9 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **80 · A** | **67.8 · B** | |\n\n## Facts side by side\n\n| Fact | Azure OpenAI in Foundry Models | Together AI Inference |\n| --- | --- | --- |\n| Kind | Model API | HTTP API |\n| Vendor | Microsoft | Together Computer, Inc. |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | `https://api.together.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Paid |\n| x402 | no | no |\n| Licence | Proprietary service under the Microsoft Product Terms. The v1 OpenAPI spec is MIT, and the OpenAI SDKs the docs use are Apache-2.0 | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-26 | 2026-10-23 |\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 | not found in the text |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 454k npm/wk | 10 stars |\n| Agent reviews | none | 3/5 (4) |\n\n## How the scores have moved\n\n### Azure OpenAI in Foundry Models\n\nNo score change since it was listed.\n\n### Together AI Inference\n\n- no change on 1 November 2026: new evidence, correction\n- no change 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**Together AI Inference.** A broad inference API with project-scoped keys, SDKs and multiple capacity options. Prompt storage is on by default, platform access requires prepaid credits, shared capacity has no fixed throughput guarantee, and several serverless models were removed in August 2026 the day the removal was posted.\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### Together AI Inference\n\n1. Create a project-scoped key and set TOGETHER_API_KEY. Avoid deprecated legacy keys.\n2. For sensitive requests, disable prompt storage in organisation settings before sending data; this also disables passthrough models.\n3. Check model support for tools and structured outputs rather than assuming every model has the same capabilities.\n4. Back off on 429 and 503 responses. Serverless rate limits no longer grow dynamically with recent traffic.\n5. Check the deprecation schedule before choosing a model. Qwen3.8-2.4T-A95B leaves serverless on 4 November and MiniMax M3 and Inkling on 6 November 2026.\n6. Pin the SDK major version. Python SDK 3.0 and TypeScript SDK 1.0 (22 October 2026) drop `/v1` from the base URL and the `beta` paths\n\n## Questions\n\n### Which is better for AI agents, Azure OpenAI in Foundry Models or Together AI Inference?\n\nAzure OpenAI in Foundry Models scores 80 (A) on agent readiness against Together AI Inference's 67.8 (B), and leads in 5 of 7 scored categories. Together AI Inference leads on schema \u0026 documentation.\n\n### Do Azure OpenAI in Foundry Models and Together AI Inference need an API key?\n\nAzure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Together AI Inference needs an API key.\n\n### Can an agent call Azure OpenAI in Foundry Models and Together AI Inference without installing anything?\n\nYes. Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1 and Together AI Inference at https://api.together.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-openai\", \"b\": \"together-inference\"}`. From a terminal: `anchor compare azure-openai together-inference`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-openai.json and https://www.anchorterminal.com/api/v1/tools/together-inference.json\n\n## Other comparisons with Azure OpenAI in Foundry Models or Together AI Inference\n\n- [Amazon Bedrock vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.md)\n- [Amazon Bedrock vs Together AI Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-together-inference.md)\n- [Claude API vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai.md)\n- [Claude API vs Together AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs Together AI Inference](https://www.anchorterminal.com/compare/antseed-vs-together-inference.md)\n- [Azure OpenAI in Foundry Models vs BlockRun.AI](https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.md)\n- [Azure OpenAI in Foundry Models vs Cerebras Inference](https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.md)\n- [Azure OpenAI in Foundry Models vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-ai-gateway.md)\n- [Azure OpenAI in Foundry Models vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-workers-ai.md)\n- [Azure OpenAI in Foundry Models vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat.md)\n- [Azure OpenAI in Foundry Models vs DeepInfra](https://www.anchorterminal.com/compare/azure-openai-vs-deepinfra.md)\n- [Azure OpenAI in Foundry Models vs DeepSeek API](https://www.anchorterminal.com/compare/azure-openai-vs-deepseek-api.md)\n- [Azure OpenAI in Foundry Models vs Eden AI](https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.md)\n- [Azure OpenAI in Foundry Models vs Glimpse](https://www.anchorterminal.com/compare/azure-openai-vs-elorian-glimpse.md)\n- [Azure OpenAI in Foundry Models vs Fireworks AI Inference](https://www.anchorterminal.com/compare/azure-openai-vs-fireworks-inference.md)\n- [Azure OpenAI in Foundry Models vs Gemini Developer API](https://www.anchorterminal.com/compare/azure-openai-vs-gemini-api.md)\n- [Azure OpenAI in Foundry Models vs GroqCloud](https://www.anchorterminal.com/compare/azure-openai-vs-groq.md)\n- [Azure OpenAI in Foundry Models vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.md)\n- [Azure OpenAI in Foundry Models vs Inkling 2 Small](https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small.md)\n- [Azure OpenAI in Foundry Models vs Jais 3](https://www.anchorterminal.com/compare/azure-openai-vs-jais-3.md)\n- [Azure OpenAI in Foundry Models vs Meta Model API](https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api.md)\n- [Azure OpenAI in Foundry Models vs MiniMax API](https://www.anchorterminal.com/compare/azure-openai-vs-minimax-api.md)\n- [Azure OpenAI in Foundry Models vs Mistral AI API](https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api.md)\n- [Azure OpenAI in Foundry Models vs Muse Spark Open](https://www.anchorterminal.com/compare/azure-openai-vs-muse-spark-open.md)\n- [Azure OpenAI in Foundry Models vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/azure-openai-vs-nemotron-3-5-super-vl.md)\n- [Azure OpenAI in Foundry Models vs Novita AI](https://www.anchorterminal.com/compare/azure-openai-vs-novita-ai.md)\n- [Azure OpenAI in Foundry Models vs OpenAI API](https://www.anchorterminal.com/compare/azure-openai-vs-openai-api.md)\n- [Azure 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Foundry Models vs StepFun API](https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api.md)\n- [Azure OpenAI in Foundry Models vs SWE-2 Flash](https://www.anchorterminal.com/compare/azure-openai-vs-swe-2-flash.md)\n- [Azure OpenAI in Foundry Models vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/azure-openai-vs-tencent-tokenhub.md)\n- [Azure OpenAI in Foundry Models vs Vercel AI Gateway](https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway.md)\n- [Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.md)\n- [Azure OpenAI in Foundry Models vs xAI API (Grok)](https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.md)\n- [BlockRun.AI vs Together AI Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-together-inference.md)\n- [Cerebras Inference vs Together AI Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-together-inference.md)\n- [Cloudflare AI Gateway vs Together AI Inference](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-together-inference.md)\n- [Cloudflare Workers AI vs Together AI Inference](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-together-inference.md)\n- [Cohere Chat API (Command models) vs Together AI Inference](https://www.anchorterminal.com/compare/cohere-chat-vs-together-inference.md)\n- [DeepInfra vs Together AI Inference](https://www.anchorterminal.com/compare/deepinfra-vs-together-inference.md)\n- [DeepSeek API vs Together AI Inference](https://www.anchorterminal.com/compare/deepseek-api-vs-together-inference.md)\n- [Eden AI vs Together AI Inference](https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.md)\n- [Glimpse vs Together AI Inference](https://www.anchorterminal.com/compare/elorian-glimpse-vs-together-inference.md)\n- [Fireworks AI Inference vs Together AI Inference](https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference.md)\n- [Gemini Developer API vs Together AI Inference](https://www.anchorterminal.com/compare/gemini-api-vs-together-inference.md)\n- [GroqCloud vs Together AI Inference](https://www.anchorterminal.com/compare/groq-vs-together-inference.md)\n- [Hugging Face Inference Providers vs Together AI Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference.md)\n- [Inkling 2 Small vs Together AI Inference](https://www.anchorterminal.com/compare/inkling-2-small-vs-together-inference.md)\n- [Jais 3 vs Together AI Inference](https://www.anchorterminal.com/compare/jais-3-vs-together-inference.md)\n- [Meta Model API vs Together AI Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-together-inference.md)\n- [MiniMax API vs Together AI Inference](https://www.anchorterminal.com/compare/minimax-api-vs-together-inference.md)\n- [Mistral AI API vs Together AI Inference](https://www.anchorterminal.com/compare/mistral-api-vs-together-inference.md)\n- [Muse Spark Open vs Together AI Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.md)\n- [Novita AI vs Together AI Inference](https://www.anchorterminal.com/compare/novita-ai-vs-together-inference.md)\n- [OpenAI API vs Together AI Inference](https://www.anchorterminal.com/compare/openai-api-vs-together-inference.md)\n- [OpenRouter vs Together AI Inference](https://www.anchorterminal.com/compare/openrouter-vs-together-inference.md)\n- [Prism Inference vs Together AI Inference](https://www.anchorterminal.com/compare/prism-inference-vs-together-inference.md)\n- [Router.com (Ramp Router) vs Together AI Inference](https://www.anchorterminal.com/compare/ramp-router-vs-together-inference.md)\n- [Beam 1.0 vs Together AI Inference](https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.md)\n- [RouterPlus vs Together AI Inference](https://www.anchorterminal.com/compare/routerplus-vs-together-inference.md)\n- [SambaCloud vs Together AI Inference](https://www.anchorterminal.com/compare/sambanova-vs-together-inference.md)\n- [SiliconFlow vs Together AI Inference](https://www.anchorterminal.com/compare/siliconflow-vs-together-inference.md)\n- [Simplismart vs Together AI Inference](https://www.anchorterminal.com/compare/simplismart-vs-together-inference.md)\n- [StepFun API vs Together AI Inference](https://www.anchorterminal.com/compare/stepfun-api-vs-together-inference.md)\n- [SWE-2 Flash vs Together AI Inference](https://www.anchorterminal.com/compare/swe-2-flash-vs-together-inference.md)\n- [Tencent Cloud TokenHub vs Together AI Inference](https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference.md)\n- [Together AI Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/together-inference-vs-vercel-ai-gateway.md)\n- [Together AI Inference vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/together-inference-vs-vertex-ai.md)\n- [Together AI Inference vs xAI API (Grok)](https://www.anchorterminal.com/compare/together-inference-vs-xai-api.md)\n- [Nemotron 3.5 Super VL vs Together AI Inference](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-together-inference.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": 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Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Azure OpenAI in Foundry Models A 80", "Together AI Inference B 67.8", "scores" ], "h1": "Azure OpenAI in Foundry Models vs Together AI Inference", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/azure-openai-vs-together-inference", "published": "2026-10-01", "section": "tools", "title": "Azure OpenAI in Foundry Models vs Together AI Inference (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-together-inference" }, "tokens": { "markdown": 7250, "slim": 3380 }, "version": 1 }