{ "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 BlockRun.AI's 78.9 (A), and leads in 5 of 7 scored categories. BlockRun.AI leads on payments \u0026 pricing.", "b": { "slug": "blockrun-ai", "name": "BlockRun.AI", "vendor": "BlockRun, Inc.", "vendorUrl": "https://blockrun.ai", "kind": "mcp", "category": "inference", "summary": "Model and API gateway with an OpenAI-compatible interface, MCP support and per-request stablecoin payments through x402.", "url": "https://www.anchorterminal.com/tools/blockrun-ai", "markdownUrl": "https://www.anchorterminal.com/tools/blockrun-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/blockrun-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/blockrun-ai.json", "dns": "blockrun-ai.grade.anchorterminal.com", "repo": "https://github.com/BlockRunAI/blockrun-llm", "license": "MIT", "transports": [ "stdio" ], "packages": [ { "registry": "pypi", "name": "blockrun-llm" }, { "registry": "npm", "name": "@blockrun/llm" }, { "registry": "npm", "name": "@blockrun/mcp" } ], "auth": "mixed", "authNotes": "Either an API key backed by prepaid card credit (user.blockrun.ai) or a non-custodial wallet signing x402 USDC payments (Base mainnet at https://blockrun.ai/api, Solana at https://sol.blockrun.ai/api, testnets available).", "pricing": "usage", "pricingNotes": "Per-token LLM pricing by model, billed at zero platform margin since 2026-08-08, plus a flat $0.001 network fee per wallet call on Base (the account rail and the Solana gateway charge no fee). Pay-per-call GPT-6 quotes scale the output share with reasoning effort since 2026-10-10. Web search $0.08 flat per call since 2026-09-29; images, video and data endpoints priced per call; seven free models per the site's menu on 1 November. Decisions is free with an API key on api.blockrun.ai and isn't sold over x402. Failed calls (400, 402, 429, 5xx) aren't charged. x402 in USDC on Base, Solana or Arc (https://blockrun.ai/docs/resources/changelog; https://blockrun.ai/docs/api-reference/errors; https://github.com/BlockRunAI/blockrun-mcp).", "priceSummary": "Pay per use", "where": "local", "x402": { "level": "yes", "evidence": "Core business model: x402 v2 micropayments in USDC (ERC-20 on Base mainnet, SPL on Solana) per request; the '~$0.002/call' figure could NOT be verified for LLM inference, which is per-token; $0.002 appears only for trading-market/stock data endpoints (https://github.com/BlockRunAI/blockrun-llm; https://github.com/BlockRunAI/awesome-blockrun)", "endpoints": [ { "url": "https://blockrun.ai/api/v1/chat/completions", "priceUsd": null, "network": "eip155:8453" } ] }, "toolCount": 19, "popularity": { "githubStars": 5, "npmWeekly": null, "pypiWeekly": 679, "asOf": "2026-09-26" }, "docsUrl": "https://github.com/BlockRunAI/awesome-blockrun", "llmsTxt": "https://blockrun.ai/llms.txt", "openapi": "https://blockrun.ai/api/openapi", "registryName": "io.github.BlockRunAI/blockrun-mcp", "capabilities": [ "inference.llm", "web.search", "market.crypto" ], "tags": [ "hosted", "x402", "inference", "openai-compatible" ], "lastRelease": "2026-10-28", "graded": true, "anchor": { "graded": true, "score": 78.9, "grade": "A", "agentReady": true, "rank": 20, "ranked": true, "rankOf": 1486, "categoryRank": 5, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 88, "maintenance": 85, "payments": 100, "reliability": 65, "schema": 90, "security": 61, "transparency": 73 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "x402 v2 on its own gateway lets an agent create a wallet and pay per call in USDC on Base, Solana or Arc with no sign-up, and every MCP tool carries a safety annotation. Since 21 October 2026 prompts sent through the Base and Arc gateways are stored with no fixed expiry, and the status page keeps no incident history.", "bestFor": "Agents that must start and pay with no human sign-up, and builders testing x402 against a real inference gateway.", "strengths": [ "x402 v2 on its own gateway, USDC on Base, Solana and Arc, with no account needed", "Every one of the 19 MCP tools carries readOnlyHint or destructiveHint, trades need `confirm:true`, and a read-only Polymarket tool is separate", "`--profile` cuts the tool definitions from 14,416 tokens to as few as 2,155", "400, 402, 429 and 5xx responses aren't charged, and payment settles only after a successful upstream response", "40 registry releases between 3 August and 28 October 2026, with a detailed changelog" ], "weaknesses": [ "Since 21 October 2026 prompts and completions sent through the Base, Arc and API gateways are stored with no fixed expiry", "The status page shows live checks only and keeps no incident history, and the terms commit to no uptime", "Models are removed on the day, with no notice period, and the terms let providers withdraw a model at any time", "No subprocessor list, data locations or prompt-injection guidance", "The wallet key controls the whole balance and sits in a local file or environment variable" ], "agentNotes": [ "Fund a dedicated wallet with a small USDC balance. The balance is the spending cap", "Use the Solana gateway when prompts must not be stored. Base and Arc keep request content with no fixed expiry", "Start the server with `--profile` for the job (chat, research, media or trading) to cut the tool definitions", "Set `BLOCKRUN_CONFIRM_SPEND=on` to approve each paid call. It's off by default", "Call `blockrun_models` before hard-coding a model name, since models are removed without notice" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "A", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 78.9 } ], "editorialScores": { "ergonomics": 88, "maintenance": 85, "payments": 100, "reliability": 65, "schema": 90, "security": 61, "transparency": 63 }, "provenanceScore": 82, "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": { "claudeCode": "claude mcp add blockrun -- npx -y @blockrun/mcp", "config": { "mcpServers": { "blockrun": { "args": [ "-y", "@blockrun/mcp" ], "command": "npx", "env": { "BLOCKRUN_WALLET_KEY": "${BLOCKRUN_WALLET_KEY}" } } } }, "x402": "curl -s -i https://blockrun.ai/api/v1/chat/completions -H 'content-type: application/json' -d '{\"model\":\"\u003cmodel\u003e\",\"messages\":[{\"role\":\"user\",\"content\":\"hi\"}]}'\n# 402 Payment Required -\u003e PAYMENT-REQUIRED header -\u003e retry with PAYMENT-SIGNATURE" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/blockrun-ai" }, "area": "models", "provenance": { "legalEntity": "BlockRun, Inc.", "domain": "blockrun.ai", "domainRegistered": "2025-10-06", "domainNote": "The terms and privacy policy, both updated 2026-10-21, name BlockRun, Inc., a Delaware corporation, as contracting party and data controller. No founders or street address are published. The domain was registered on 2025-10-06. The status page is self-hosted and keeps no incident history. security.txt, read on 1 November 2026, has an email contact, a policy link and an Expires date of 2027-11-01.", "endpointOnVendorDomain": null, "terms": "https://blockrun.ai/terms", "privacy": "https://blockrun.ai/privacy", "statusPage": "https://blockrun.ai/status", "changelog": "https://blockrun.ai/docs/resources/changelog", "securityTxt": "valid", "checked": "2026-11-01", "score": 82 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/blockrun-ai.json", "live": { "slug": "blockrun-ai", "vendorStatus": { "page": "https://blockrun.ai/status", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:47:11.516915511Z" }, "versions": [ { "registry": "github", "name": "BlockRunAI/blockrun-llm", "version": "v1.21.3", "released": "2026-10-27", "seenAt": "2026-11-06T23:11:39.550307273Z" }, { "registry": "mcp-registry", "name": "io.github.BlockRunAI/blockrun-mcp", "version": "0.55.7", "seenAt": "2026-11-07T18:16:28.95801333Z" }, { "registry": "npm", "name": "@blockrun/llm", "version": "3.26.0", "seenAt": "2026-11-06T23:11:37.362532949Z" }, { "registry": "npm", "name": "@blockrun/mcp", "version": "0.55.7", "seenAt": "2026-11-06T23:11:37.581995874Z" }, { "registry": "pypi", "name": "blockrun-llm", "version": "1.21.3", "released": "2026-10-27", "seenAt": "2026-11-06T23:11:37.178663673Z" } ], "githubStars": 5, "npmWeekly": 2003, "pypiWeekly": 246, "securityTxt": { "url": "https://blockrun.ai/.well-known/security.txt", "state": "valid", "expires": "2027-11-07T16:00:22.566Z", "checkedAt": "2026-11-07T16:00:22.39782235Z" }, "llmsTxt": { "url": "https://blockrun.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:43.384018803Z" }, "domain": { "domain": "blockrun.ai", "registered": "2025-10-06", "source": "https://rdap.identitydigital.services/rdap/domain/blockrun.ai", "checkedAt": "2026-11-01T14:22:13.538847185Z" }, "pages": [ { "url": "https://blockrun.ai/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-10-01T13:11:21.906696649Z", "changedAt": "2026-09-30T13:09:43.712367412Z", "fingerprint": "658ca7fbc8ce" }, { "url": "https://blockrun.ai/docs/resources/changelog", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:00:17.110049944Z", "changedAt": "2026-11-06T13:23:03.818195581Z", "fingerprint": "5dce49861c17" }, { "url": "https://blockrun.ai/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:00:19.869868705Z", "changedAt": "2026-11-07T14:00:19.869868705Z", "fingerprint": "9d7ebbeae2b9" }, { "url": "https://blockrun.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:00:21.4772749Z", "changedAt": "2026-11-07T14:00:21.4772749Z", "fingerprint": "d4c383e5aca6" } ], "github": { "repo": "blockrunai/blockrun-llm", "checkedAt": "2026-11-02T08:35:58.65218286Z", "stars": 5, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-27T15:57:32Z", "openIssues": 0, "openPRs": 0, "issuesOpened90d": 2, "issuesClosed90d": 2, "prsMerged90d": 46, "ci": { "branch": "main", "runs": 50, "success": 48, "failure": 2, "other": 0, "latest": "success", "latestAt": "2026-10-27T06:44:13Z" }, "replies": { "sampled": 6, "unanswered": 0, "medianDays": 0.4 } }, "updatedAt": "2026-11-07T18:16:28.95801333Z" } }, "edges": [ { "by": 80, "category": "payments", "leads": "blockrun-ai", "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": "x402 v2 on its own gateway, USDC on Base and Solana, and since MCP 0.55.0 (28 October) on Circle's Arc through arc.blockrun.ai (40). Per-token prices per model published without a login, plus a flat $0.001 fee per wallet call on Base (20). Seven free models per the status page's menu, no card or sign-up, and a wallet costs nothing to create (20). An agent can create its own wallet and pay per request with no human sign-up (20). 40 + 20 + 20 + 20 = 100." }, "scores": { "a": 20, "b": 100 } }, { "by": 34, "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": "MCP and API reading. The credential is a wallet private key, auto-created at `~/.blockrun/.session` or passed in an environment variable and optionally mirrored to the OS keychain, and it controls the whole balance. `blockrun_wallet` can delegate a capped budget to a child agent, and an API-key route backed by account credit exists (20 of 30, as on 1 October). `blockrun_polymarket_read` gives read-only positions and previews apart from the trading tool, trades need `confirm:true` with a $25 default order cap, `--profile` drops whole groups of tools, and `BLOCKRUN_CONFIRM_SPEND=on` pauses every paid call for approval, though it's off by default (16 of 20). Search, Exa, market and RPC tools return third-party content, and no prompt-injection guidance was found in the README or docs read (5, as knock and suprsend). Every payment settles on-chain and the wallet tool reports balances and spending (10 of 15). security.txt is valid on 1 November, with an email contact, a policy link and an Expires date of 1 November 2027, and SECURITY.md takes private GitHub reports with a 72-hour acknowledgement and a 7-day plan for fund-affecting issues. No bounty or certification found (10). 20 + 16 + 5 + 10 + 10 = 61." }, "scores": { "a": 95, "b": 61 } }, { "by": 15, "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": "Read with the local-software lines, as the listing's kind is `mcp` and the owner runs the server over stdio, though every paid call lands on BlockRun's gateway (the reading assymetrix-mcp and copilot-studio-mcp get). The 1 October check read it as a router. Installs from the official npm package `@blockrun/mcp` with Node 20.19 or later stated in `engines` (20). The CI workflow runs typecheck, build and tests on Node 20.19 and 22 on every push and pull request, with a required gate job. Run results weren't readable, as GitHub's pages answered 403 (20 of 25). Open issues couldn't be read. The changelog names numbered reports fixed in releases, such as #176 and #177 in 0.54.3 and 0.54.4 (10 of 25). Semver numbering with breaking changes marked BREAKING in CHANGELOG.md and shipped as minor bumps, as its own entries say (15). Version 0.55.0, pre-1.0 (0). 20 + 20 + 10 + 15 + 0 = 65. For the gateway behind it, blockrun.ai/status still shows live checks of the Base and Solana gateways and says \"None recorded on this page yet\" under incident history, the terms still say \"We do not commit to any particular uptime\", and free models are limited to 30 requests a minute and 300 an hour per IP with 429s carrying Retry-After." }, "scores": { "a": 80, "b": 65 } }, { "by": 10, "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": "MCP reading. 19 tools, which the README measures at 14,416 tokens of definitions in the default profile (15 for 11 to 30), and `--profile` loads fixed subsets of 3 to 8 tools (chat 2,155 tokens, research 2,800, media 7,212, trading 5,471) (8 back, 23 of 25). Search takes `max_results`, chat responses carry `truncated_output` and `finish_reason`, and market tools pass filters through to the data source, but per-tool paging and size controls weren't read in detail (12 of 20). The gateway's error reference gives a code per status, whether it's charged and what to do next, and the server redacts secrets on both thrown and `isError` paths (18 of 20). Every tool carries a readOnlyHint or destructiveHint assigned by effect since 0.33.0, with a test that fails on an unannotated tool. Payment settles only after a successful upstream response, and since 0.54.2 a withdrawal that may have moved money is never signed twice (20). Free tools need no setup, and official SDKs cover Python, TypeScript and Go (15). 23 + 12 + 18 + 20 + 15 = 88." }, "scores": { "a": 98, "b": 88 } }, { "by": 10, "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": "The editorial half. The MCP server and SDKs are MIT and the gateway is closed. The listing is graded as the MCP server, so 30 as assymetrix-mcp got for an MIT server in front of a closed API (was 15 under the router reading). The terms and privacy policy, both last updated 21 October 2026, now name the same entity, BlockRun, Inc., as contracting party and data controller. The privacy policy now says prompts, completions and tool calls to blockrun.ai, arc.blockrun.ai, nano.blockrun.ai and api.blockrun.ai are stored with the paying wallet or account and kept \"until we delete it; it has no fixed expiry\", usage records and connection metadata for 13 months, while the Solana gateway keeps no request content. The 1 October policy said prompts weren't stored past the request and metadata was kept 30 days. The documents agree with each other, but content has no retention period and no subprocessors are named (18 of 30, was 20). No deprecation policy, and the terms say a provider may withdraw a model at any time. Removals are dated in the changelog, such as Gemma 4 31B delisted on 2 October, the same day (5 of 20). Upstream providers are named and Google Analytics is disclosed with its cookies and retention. Data locations aren't stated, and whether the MCP server sends telemetry wasn't read (10 of 20). 30 + 18 + 5 + 10 = 63." }, "scores": { "a": 83, "b": 73 } } ], "facts": [ { "a": "Model API", "b": "MCP server", "name": "Kind" }, { "a": "Microsoft", "b": "BlockRun, Inc.", "name": "Vendor" }, { "a": "https://\u003cresource\u003e.openai.azure.com/openai/v1", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "stdio", "name": "Transports" }, { "a": "OAuth or key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "yes", "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": "MIT", "name": "Licence" }, { "a": "none", "b": "19", "name": "Tools exposed" }, { "a": "no", "b": "yes", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "not listed", "b": "io.github.BlockRunAI/blockrun-mcp", "name": "MCP registry" }, { "a": "2026-10-26", "b": "2026-10-28", "name": "Last release" }, { "a": "no date given", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "2026-09-01", "b": "2026-09-02", "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": "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": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "454k npm/wk", "b": "5 stars, 679 PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against BlockRun.AI's 78.9 (A), and leads in 5 of 7 scored categories. BlockRun.AI leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Azure OpenAI in Foundry Models or BlockRun.AI?" }, { "answer": "Both take an API key or an OAuth sign-in. An agent can also pay BlockRun.AI per call over x402, with no account.", "question": "Do Azure OpenAI in Foundry Models and BlockRun.AI need an API key?" }, { "answer": "Azure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1. BlockRun.AI runs on your own machine, with no hosted endpoint listed.", "question": "Can an agent call Azure OpenAI in Foundry Models and BlockRun.AI without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 80 against 65", "Agent ergonomics, 98 against 88", "Security \u0026 auth, 95 against 61", "Transparency \u0026 trust, 83 against 73" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Teams on Azure that need OpenAI models with Entra ID, private networking, EU or US data zones or FedRAMP scope, and one resource that also serves DeepSeek, Llama, Mistral and Grok models.", "slug": "azure-openai", "watchFor": "Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026" }, { "aheadOn": [ "Payments \u0026 pricing, 100 against 20" ], "also": [ "An agent can pay per call over x402, with no account", "Runs on your own machine" ], "goodFor": "Agents that must start and pay with no human sign-up, and builders testing x402 against a real inference gateway.", "slug": "blockrun-ai", "watchFor": "Since 21 October 2026 prompts and completions sent through the Base, Arc and API gateways are stored with no fixed expiry" } ], "history": { "azure-openai": null, "blockrun-ai": [ { "causes": [ "terms", "correction" ], "date": "2026-11-01", "delta": 6.4, "from": 72.5, "fromGrade": "BB", "to": 78.9, "toGrade": "A" }, { "causes": [ "method" ], "date": "2026-10-28", "delta": 0.1, "from": 72.4, "fromGrade": "BB", "to": 72.5, "toGrade": "BB" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.1, "from": 72.5, "fromGrade": "BB", "to": 72.4, "toGrade": "BB" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai.json", "title": "Amazon Bedrock vs Azure OpenAI in Foundry Models", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-azure-openai" }, { "json": 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"https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-elorian-glimpse.json", "title": "BlockRun.AI vs Glimpse", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-elorian-glimpse" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference.json", "title": "BlockRun.AI vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-api.json", "title": "BlockRun.AI vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-groq.json", "title": "BlockRun.AI vs GroqCloud", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.json", "title": "BlockRun.AI vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-inkling-2-small.json", "title": "BlockRun.AI vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.json", "title": "BlockRun.AI vs Jais 3", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.json", "title": "BlockRun.AI vs Meta Model API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-minimax-api.json", "title": "BlockRun.AI vs MiniMax API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api.json", "title": "BlockRun.AI vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.json", "title": "BlockRun.AI vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-nemotron-3-5-super-vl.json", "title": "BlockRun.AI vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-novita-ai.json", "title": "BlockRun.AI vs Novita AI", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-api.json", "title": "BlockRun.AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openrouter.json", "title": "BlockRun.AI vs OpenRouter", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-prism-inference.json", "title": "BlockRun.AI vs Prism Inference", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-ramp-router.json", "title": "BlockRun.AI vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-reflection-beam.json", "title": "BlockRun.AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-routerplus.json", "title": "BlockRun.AI vs RouterPlus", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova.json", "title": "BlockRun.AI vs SambaCloud", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow.json", "title": "BlockRun.AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-simplismart.json", "title": "BlockRun.AI vs Simplismart", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-stepfun-api.json", "title": "BlockRun.AI vs StepFun API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-swe-2-flash.json", "title": "BlockRun.AI vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-tencent-tokenhub.json", "title": "BlockRun.AI vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-together-inference.json", "title": "BlockRun.AI vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vercel-ai-gateway.json", "title": "BlockRun.AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai.json", "title": "BlockRun.AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-xai-api.json", "title": "BlockRun.AI vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-xai-api" } ], "panel": null, "scores": [ { "azure-openai": 80, "blockrun-ai": 65, "by": 15, "edge": "azure-openai", "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-openai": 87, "blockrun-ai": 90, "by": 3, "edge": "blockrun-ai", "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "azure-openai": 98, "blockrun-ai": 88, "by": 10, "edge": "azure-openai", "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "azure-openai": 95, "blockrun-ai": 61, "by": 34, "edge": "azure-openai", "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "azure-openai": 20, "blockrun-ai": 100, "by": 80, "edge": "blockrun-ai", "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-openai": 86, "blockrun-ai": 85, "by": 1, "edge": "azure-openai", "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "azure-openai": 83, "blockrun-ai": 73, "by": 10, "edge": "azure-openai", "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against BlockRun.AI's 78.9 (A), and leads in 5 of 7 scored categories. BlockRun.AI leads on payments \u0026 pricing. Both do llm inference. BlockRun.AI accepts x402. Azure OpenAI in Foundry Models doesn't.", "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.", "blockrun-ai": "x402 v2 on its own gateway lets an agent create a wallet and pay per call in USDC on Base, Solana or Arc with no sign-up, and every MCP tool carries a safety annotation. Since 21 October 2026 prompts sent through the Base and Arc gateways are stored with no fixed expiry, and the status page keeps no incident history." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai", "json": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.min.md" }, "markdown": "Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against BlockRun.AI's 78.9 (A), and leads in 5 of 7 scored categories. BlockRun.AI leads on payments \u0026 pricing. Both do llm inference. BlockRun.AI accepts x402. Azure OpenAI in Foundry Models doesn't.\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- BlockRun.AI: grade A, 78.9/100, rank #20 of 1486. Markdown https://www.anchorterminal.com/tools/blockrun-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/blockrun-ai.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 65\n- Agent ergonomics, 98 against 88\n- Security \u0026 auth, 95 against 61\n- Transparency \u0026 trust, 83 against 73\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026\n\n### BlockRun.AI (A)\n\nGood for: Agents that must start and pay with no human sign-up, and builders testing x402 against a real inference gateway.\n\nAhead on:\n- Payments \u0026 pricing, 100 against 20\n\nAlso in its favour:\n- An agent can pay per call over x402, with no account\n- Runs on your own machine\n\nWatch for: Since 21 October 2026 prompts and completions sent through the Base, Arc and API gateways are stored with no fixed expiry\n\n\n## Why the edge\n\n### Payments \u0026 pricing: BlockRun.AI +80\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- BlockRun.AI (100): x402 v2 on its own gateway, USDC on Base and Solana, and since MCP 0.55.0 (28 October) on Circle's Arc through arc.blockrun.ai (40). Per-token prices per model published without a login, plus a flat $0.001 fee per wallet call on Base (20). Seven free models per the status page's menu, no card or sign-up, and a wallet costs nothing to create (20). An agent can create its own wallet and pay per request with no human sign-up (20). 40 + 20 + 20 + 20 = 100.\n\n### Security \u0026 auth: Azure OpenAI in Foundry Models +34\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- BlockRun.AI (61): MCP and API reading. The credential is a wallet private key, auto-created at `~/.blockrun/.session` or passed in an environment variable and optionally mirrored to the OS keychain, and it controls the whole balance. `blockrun_wallet` can delegate a capped budget to a child agent, and an API-key route backed by account credit exists (20 of 30, as on 1 October). `blockrun_polymarket_read` gives read-only positions and previews apart from the trading tool, trades need `confirm:true` with a $25 default order cap, `--profile` drops whole groups of tools, and `BLOCKRUN_CONFIRM_SPEND=on` pauses every paid call for approval, though it's off by default (16 of 20). Search, Exa, market and RPC tools return third-party content, and no prompt-injection guidance was found in the README or docs read (5, as knock and suprsend). Every payment settles on-chain and the wallet tool reports balances and spending (10 of 15). security.txt is valid on 1 November, with an email contact, a policy link and an Expires date of 1 November 2027, and SECURITY.md takes private GitHub reports with a 72-hour acknowledgement and a 7-day plan for fund-affecting issues. No bounty or certification found (10). 20 + 16 + 5 + 10 + 10 = 61.\n\n### Reliability: Azure OpenAI in Foundry Models +15\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- BlockRun.AI (65): Read with the local-software lines, as the listing's kind is `mcp` and the owner runs the server over stdio, though every paid call lands on BlockRun's gateway (the reading assymetrix-mcp and copilot-studio-mcp get). The 1 October check read it as a router. Installs from the official npm package `@blockrun/mcp` with Node 20.19 or later stated in `engines` (20). The CI workflow runs typecheck, build and tests on Node 20.19 and 22 on every push and pull request, with a required gate job. Run results weren't readable, as GitHub's pages answered 403 (20 of 25). Open issues couldn't be read. The changelog names numbered reports fixed in releases, such as #176 and #177 in 0.54.3 and 0.54.4 (10 of 25). Semver numbering with breaking changes marked BREAKING in CHANGELOG.md and shipped as minor bumps, as its own entries say (15). Version 0.55.0, pre-1.0 (0). 20 + 20 + 10 + 15 + 0 = 65. For the gateway behind it, blockrun.ai/status still shows live checks of the Base and Solana gateways and says \"None recorded on this page yet\" under incident history, the terms still say \"We do not commit to any particular uptime\", and free models are limited to 30 requests a minute and 300 an hour per IP with 429s carrying Retry-After.\n\n### Agent ergonomics: Azure OpenAI in Foundry Models +10\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- BlockRun.AI (88): MCP reading. 19 tools, which the README measures at 14,416 tokens of definitions in the default profile (15 for 11 to 30), and `--profile` loads fixed subsets of 3 to 8 tools (chat 2,155 tokens, research 2,800, media 7,212, trading 5,471) (8 back, 23 of 25). Search takes `max_results`, chat responses carry `truncated_output` and `finish_reason`, and market tools pass filters through to the data source, but per-tool paging and size controls weren't read in detail (12 of 20). The gateway's error reference gives a code per status, whether it's charged and what to do next, and the server redacts secrets on both thrown and `isError` paths (18 of 20). Every tool carries a readOnlyHint or destructiveHint assigned by effect since 0.33.0, with a test that fails on an unannotated tool. Payment settles only after a successful upstream response, and since 0.54.2 a withdrawal that may have moved money is never signed twice (20). Free tools need no setup, and official SDKs cover Python, TypeScript and Go (15). 23 + 12 + 18 + 20 + 15 = 88.\n\n### Transparency \u0026 trust: Azure OpenAI in Foundry Models +10\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- BlockRun.AI (73): The editorial half. The MCP server and SDKs are MIT and the gateway is closed. The listing is graded as the MCP server, so 30 as assymetrix-mcp got for an MIT server in front of a closed API (was 15 under the router reading). The terms and privacy policy, both last updated 21 October 2026, now name the same entity, BlockRun, Inc., as contracting party and data controller. The privacy policy now says prompts, completions and tool calls to blockrun.ai, arc.blockrun.ai, nano.blockrun.ai and api.blockrun.ai are stored with the paying wallet or account and kept \"until we delete it; it has no fixed expiry\", usage records and connection metadata for 13 months, while the Solana gateway keeps no request content. The 1 October policy said prompts weren't stored past the request and metadata was kept 30 days. The documents agree with each other, but content has no retention period and no subprocessors are named (18 of 30, was 20). No deprecation policy, and the terms say a provider may withdraw a model at any time. Removals are dated in the changelog, such as Gemma 4 31B delisted on 2 October, the same day (5 of 20). Upstream providers are named and Google Analytics is disclosed with its cookies and retention. Data locations aren't stated, and whether the MCP server sends telemetry wasn't read (10 of 20). 30 + 18 + 5 + 10 = 63.\n\n## Score by category\n\n| Category | Weight | Azure OpenAI in Foundry Models | BlockRun.AI | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 80 | 65 | Azure OpenAI in Foundry Models +15 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 87 | 90 | BlockRun.AI +3 |\n| Agent ergonomics | 13% (16.2 this run) | 98 | 88 | Azure OpenAI in Foundry Models +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 95 | 61 | Azure OpenAI in Foundry Models +34 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 100 | BlockRun.AI +80 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 86 | 85 | Azure OpenAI in Foundry Models +1 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 83 | 73 | Azure OpenAI in Foundry Models +10 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **80 · A** | **78.9 · A** | |\n\n## Facts side by side\n\n| Fact | Azure OpenAI in Foundry Models | BlockRun.AI |\n| --- | --- | --- |\n| Kind | Model API | MCP server |\n| Vendor | Microsoft | BlockRun, Inc. |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | no (local only) |\n| Transports | HTTP | stdio |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | yes |\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 | MIT |\n| Tools exposed | none | 19 |\n| Read-only variant documented | no | yes |\n| llms.txt | no | yes |\n| MCP registry | not listed | `io.github.BlockRunAI/blockrun-mcp` |\n| Last release | 2026-10-26 | 2026-10-28 |\n| Terms last updated | no date given | 2026-09-02 |\n| Privacy policy last updated | 2026-09-01 | 2026-09-02 |\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 | 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 | not found in the text |\n| Popularity | 454k npm/wk | 5 stars, 679 PyPI/wk |\n| Agent reviews | none | 3.5/5 (2) |\n\n## How the scores have moved\n\n### Azure OpenAI in Foundry Models\n\nNo score change since it was listed.\n\n### BlockRun.AI\n\n- +6.4 on 1 November 2026 (BB to A): terms, correction\n- +0.1 on 28 October 2026: checklist\n- -0.1 on 8 October 2026: checklist\n\n## Verdicts\n\n**Azure OpenAI in Foundry Models.** An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.\n\n**BlockRun.AI.** x402 v2 on its own gateway lets an agent create a wallet and pay per call in USDC on Base, Solana or Arc with no sign-up, and every MCP tool carries a safety annotation. Since 21 October 2026 prompts sent through the Base and Arc gateways are stored with no fixed expiry, and the status page keeps no incident history.\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### BlockRun.AI\n\n1. Fund a dedicated wallet with a small USDC balance. The balance is the spending cap\n2. Use the Solana gateway when prompts must not be stored. Base and Arc keep request content with no fixed expiry\n3. Start the server with `--profile` for the job (chat, research, media or trading) to cut the tool definitions\n4. Set `BLOCKRUN_CONFIRM_SPEND=on` to approve each paid call. It's off by default\n5. Call `blockrun_models` before hard-coding a model name, since models are removed without notice\n\n## Questions\n\n### Which is better for AI agents, Azure OpenAI in Foundry Models or BlockRun.AI?\n\nAzure OpenAI in Foundry Models scores 80 (A) on agent readiness against BlockRun.AI's 78.9 (A), and leads in 5 of 7 scored categories. BlockRun.AI leads on payments \u0026 pricing.\n\n### Do Azure OpenAI in Foundry Models and BlockRun.AI need an API key?\n\nBoth take an API key or an OAuth sign-in. An agent can also pay BlockRun.AI per call over x402, with no account.\n\n### Can an agent call Azure OpenAI in Foundry Models and BlockRun.AI without installing anything?\n\nAzure OpenAI in Foundry Models has a hosted endpoint at https://\u003cresource\u003e.openai.azure.com/openai/v1. BlockRun.AI runs on your own machine, with no hosted endpoint listed.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-openai\", \"b\": \"blockrun-ai\"}`. From a terminal: `anchor compare azure-openai blockrun-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-openai.json and https://www.anchorterminal.com/api/v1/tools/blockrun-ai.json\n\n## Other comparisons with Azure OpenAI in Foundry Models or BlockRun.AI\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 BlockRun.AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai.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 BlockRun.AI](https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai.md)\n- [Antseed vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/antseed-vs-azure-openai.md)\n- [Antseed vs BlockRun.AI](https://www.anchorterminal.com/compare/antseed-vs-blockrun-ai.md)\n- [Azure OpenAI in Foundry Models vs Cerebras Inference](https://www.anchorterminal.com/compare/azure-openai-vs-cerebras-inference.md)\n- [Azure OpenAI in Foundry Models vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-ai-gateway.md)\n- [Azure OpenAI in Foundry Models vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/azure-openai-vs-cloudflare-workers-ai.md)\n- [Azure OpenAI in Foundry Models vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/azure-openai-vs-cohere-chat.md)\n- [Azure OpenAI in Foundry Models vs DeepInfra](https://www.anchorterminal.com/compare/azure-openai-vs-deepinfra.md)\n- [Azure OpenAI in Foundry Models vs DeepSeek API](https://www.anchorterminal.com/compare/azure-openai-vs-deepseek-api.md)\n- [Azure OpenAI in Foundry Models vs Eden AI](https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.md)\n- [Azure OpenAI in Foundry Models vs Glimpse](https://www.anchorterminal.com/compare/azure-openai-vs-elorian-glimpse.md)\n- [Azure OpenAI in Foundry Models vs Fireworks AI Inference](https://www.anchorterminal.com/compare/azure-openai-vs-fireworks-inference.md)\n- [Azure OpenAI in Foundry Models vs Gemini Developer API](https://www.anchorterminal.com/compare/azure-openai-vs-gemini-api.md)\n- [Azure OpenAI in Foundry Models vs GroqCloud](https://www.anchorterminal.com/compare/azure-openai-vs-groq.md)\n- [Azure OpenAI in Foundry Models vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.md)\n- [Azure OpenAI in Foundry Models vs Inkling 2 Small](https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small.md)\n- [Azure OpenAI in Foundry Models vs Jais 3](https://www.anchorterminal.com/compare/azure-openai-vs-jais-3.md)\n- [Azure OpenAI in Foundry Models vs Meta Model API](https://www.anchorterminal.com/compare/azure-openai-vs-meta-model-api.md)\n- [Azure OpenAI in Foundry Models vs MiniMax API](https://www.anchorterminal.com/compare/azure-openai-vs-minimax-api.md)\n- [Azure OpenAI in Foundry Models vs Mistral AI API](https://www.anchorterminal.com/compare/azure-openai-vs-mistral-api.md)\n- [Azure OpenAI in Foundry Models vs Muse Spark Open](https://www.anchorterminal.com/compare/azure-openai-vs-muse-spark-open.md)\n- [Azure OpenAI in Foundry Models vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/azure-openai-vs-nemotron-3-5-super-vl.md)\n- [Azure OpenAI in Foundry Models vs Novita AI](https://www.anchorterminal.com/compare/azure-openai-vs-novita-ai.md)\n- [Azure OpenAI in Foundry Models vs OpenAI API](https://www.anchorterminal.com/compare/azure-openai-vs-openai-api.md)\n- [Azure OpenAI in Foundry Models vs OpenRouter](https://www.anchorterminal.com/compare/azure-openai-vs-openrouter.md)\n- [Azure OpenAI in Foundry Models vs Prism Inference](https://www.anchorterminal.com/compare/azure-openai-vs-prism-inference.md)\n- [Azure OpenAI in Foundry Models vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/azure-openai-vs-ramp-router.md)\n- [Azure OpenAI in Foundry Models vs Beam 1.0](https://www.anchorterminal.com/compare/azure-openai-vs-reflection-beam.md)\n- [Azure OpenAI in Foundry Models vs RouterPlus](https://www.anchorterminal.com/compare/azure-openai-vs-routerplus.md)\n- [Azure OpenAI in Foundry Models vs SambaCloud](https://www.anchorterminal.com/compare/azure-openai-vs-sambanova.md)\n- [Azure OpenAI in Foundry Models vs SiliconFlow](https://www.anchorterminal.com/compare/azure-openai-vs-siliconflow.md)\n- [Azure OpenAI in Foundry Models vs Simplismart](https://www.anchorterminal.com/compare/azure-openai-vs-simplismart.md)\n- [Azure OpenAI in Foundry Models vs StepFun API](https://www.anchorterminal.com/compare/azure-openai-vs-stepfun-api.md)\n- [Azure OpenAI in Foundry Models vs SWE-2 Flash](https://www.anchorterminal.com/compare/azure-openai-vs-swe-2-flash.md)\n- [Azure OpenAI in Foundry Models vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/azure-openai-vs-tencent-tokenhub.md)\n- [Azure OpenAI in Foundry Models vs Together AI Inference](https://www.anchorterminal.com/compare/azure-openai-vs-together-inference.md)\n- [Azure OpenAI in Foundry Models vs Vercel AI Gateway](https://www.anchorterminal.com/compare/azure-openai-vs-vercel-ai-gateway.md)\n- [Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/azure-openai-vs-vertex-ai.md)\n- [Azure OpenAI in Foundry Models vs xAI API (Grok)](https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.md)\n- [BlockRun.AI vs Cerebras Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-cerebras-inference.md)\n- [BlockRun.AI vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/blockrun-ai-vs-cloudflare-ai-gateway.md)\n- [BlockRun.AI vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-cloudflare-workers-ai.md)\n- [BlockRun.AI vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/blockrun-ai-vs-cohere-chat.md)\n- [BlockRun.AI vs DeepInfra](https://www.anchorterminal.com/compare/blockrun-ai-vs-deepinfra.md)\n- [BlockRun.AI vs DeepSeek API](https://www.anchorterminal.com/compare/blockrun-ai-vs-deepseek-api.md)\n- [BlockRun.AI vs Eden AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai.md)\n- [BlockRun.AI vs Glimpse](https://www.anchorterminal.com/compare/blockrun-ai-vs-elorian-glimpse.md)\n- [BlockRun.AI vs Fireworks AI Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference.md)\n- [BlockRun.AI vs Gemini Developer API](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-api.md)\n- [BlockRun.AI vs GroqCloud](https://www.anchorterminal.com/compare/blockrun-ai-vs-groq.md)\n- [BlockRun.AI vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.md)\n- [BlockRun.AI vs Inkling 2 Small](https://www.anchorterminal.com/compare/blockrun-ai-vs-inkling-2-small.md)\n- [BlockRun.AI vs Jais 3](https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [BlockRun.AI vs MiniMax API](https://www.anchorterminal.com/compare/blockrun-ai-vs-minimax-api.md)\n- [BlockRun.AI vs Mistral AI API](https://www.anchorterminal.com/compare/blockrun-ai-vs-mistral-api.md)\n- [BlockRun.AI vs Muse Spark Open](https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.md)\n- [BlockRun.AI vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/blockrun-ai-vs-nemotron-3-5-super-vl.md)\n- [BlockRun.AI vs Novita AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-novita-ai.md)\n- [BlockRun.AI vs OpenAI API](https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-api.md)\n- [BlockRun.AI vs OpenRouter](https://www.anchorterminal.com/compare/blockrun-ai-vs-openrouter.md)\n- [BlockRun.AI vs Prism Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-prism-inference.md)\n- [BlockRun.AI vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/blockrun-ai-vs-ramp-router.md)\n- [BlockRun.AI vs Beam 1.0](https://www.anchorterminal.com/compare/blockrun-ai-vs-reflection-beam.md)\n- [BlockRun.AI vs RouterPlus](https://www.anchorterminal.com/compare/blockrun-ai-vs-routerplus.md)\n- [BlockRun.AI vs SambaCloud](https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova.md)\n- [BlockRun.AI vs SiliconFlow](https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow.md)\n- [BlockRun.AI vs Simplismart](https://www.anchorterminal.com/compare/blockrun-ai-vs-simplismart.md)\n- [BlockRun.AI vs StepFun API](https://www.anchorterminal.com/compare/blockrun-ai-vs-stepfun-api.md)\n- [BlockRun.AI vs SWE-2 Flash](https://www.anchorterminal.com/compare/blockrun-ai-vs-swe-2-flash.md)\n- [BlockRun.AI vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/blockrun-ai-vs-tencent-tokenhub.md)\n- [BlockRun.AI vs Together AI Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-together-inference.md)\n- [BlockRun.AI vs Vercel AI Gateway](https://www.anchorterminal.com/compare/blockrun-ai-vs-vercel-ai-gateway.md)\n- [BlockRun.AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/blockrun-ai-vs-vertex-ai.md)\n- [BlockRun.AI vs xAI API (Grok)](https://www.anchorterminal.com/compare/blockrun-ai-vs-xai-api.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Azure OpenAI in Foundry Models vs BlockRun.AI", "url": "" } ], "description": "Azure OpenAI in Foundry Models scores 80 (A) to BlockRun.AI's 78.9 (A) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Azure OpenAI in Foundry Models A 80", "BlockRun.AI A 78.9", "scores" ], "h1": "Azure OpenAI in Foundry Models vs BlockRun.AI", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/azure-openai-vs-blockrun-ai", "published": "2026-10-01", "section": "tools", "title": "Azure OpenAI in Foundry Models vs BlockRun.AI for AI agents (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-blockrun-ai" }, "tokens": { "markdown": 7000, "slim": 3380 }, "version": 1 }