{
  "data": {
    "a": {
      "slug": "azure-foundry-fine-tuning",
      "name": "Microsoft Foundry fine-tuning (Azure OpenAI)",
      "vendor": "Microsoft Azure",
      "vendorUrl": "https://azure.microsoft.com",
      "kind": "http-api",
      "category": "fine-tuning",
      "summary": "Azure's managed service for supervised, preference and reinforcement fine-tuning of supported OpenAI and open-weight models.",
      "url": "https://www.anchorterminal.com/tools/azure-foundry-fine-tuning",
      "markdownUrl": "https://www.anchorterminal.com/tools/azure-foundry-fine-tuning.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/azure-foundry-fine-tuning.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/azure-foundry-fine-tuning.json",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://\u003cresource\u003e.openai.azure.com/openai/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "openai"
        },
        {
          "registry": "npm",
          "name": "openai"
        }
      ],
      "auth": "mixed",
      "authNotes": "`api-key` header with a resource key, or a Microsoft Entra ID bearer token. Training a model needs the Foundry User role and deploying it needs Foundry Owner (renamed from Azure AI User and Azure AI Owner). Deployments are created through the Azure Resource Manager API at management.azure.com, a second credential.",
      "pricing": "usage",
      "pricingNotes": "SFT and DPO bill training tokens x epochs at a per-model rate. The Azure Retail Prices API lists, per 1M training tokens, gpt-4.1 at $25 global and $30.25 regional, gpt-4.1-mini at $5 and $6.05, and gpt-4.1-nano at $1.50 and $1.815 (regional is 21 per cent above global). RFT bills training hours plus grader tokens; the cost guide's example uses $100 an hour for o4-mini and jobs pause at $5,000. The developer tier is 50 per cent below global on pre-emptible capacity, without data residency. A fine-tuned model on a Standard or Global Standard deployment costs $1.70 an hour to host plus per-token inference (gpt-4.1-ft $2 input and $8 output per 1M, global); developer deployments have no hosting fee and are deleted after 24 hours (https://prices.azure.com/api/retail/prices, https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning-cost-management).",
      "priceSummary": "Pay per use",
      "where": "hosted",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": 47155661,
        "pypiWeekly": 72103251,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/fine-tuning",
      "capabilities": [
        "finetune.sft",
        "finetune.preference",
        "finetune.rl",
        "finetune.lora"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "closed-source",
        "card-required",
        "enterprise",
        "eu",
        "python",
        "typescript",
        "async-jobs"
      ],
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61.4,
        "grade": "C",
        "agentReady": false,
        "rank": 228,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 2,
        "methodology": "0.3",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 47,
          "maintenance": 55,
          "payments": 20,
          "reliability": 65,
          "schema": 67,
          "security": 85,
          "transparency": 88
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "SFT, DPO and RFT on GPT-4.1 and o4-mini through the OpenAI-shaped /openai/v1 API. No weight export; checkpoints copy only between Azure resources.",
        "strengths": [
          "SFT, DPO and RFT on GPT-4.1 and o4-mini through the OpenAI-shaped /openai/v1 API",
          "Retirement policy with 60 days' notice and published training and deployment retirement dates per tunable model",
          "Entra ID with RBAC, Azure Monitor logs and an activity log for every customer",
          "Training files and tuned models stay in the resource's geography, are deletable and exclusive to the customer",
          "Fine-tuning limits published with numbers, from 3 concurrent jobs to 2 billion tokens per job"
        ],
        "weaknesses": [
          "No weight export; checkpoints copy only between Azure resources",
          "$1.70 an hour hosting on Standard deployments, and deletion after 15 idle days",
          "GPT-4.1 training at $25 per 1M tokens globally, and no free tier without a card",
          "Deployment goes through management.azure.com with a separate credential and the Foundry Owner role",
          "The Azure OpenAI 'what's new' page hasn't had a dated section since May 2026"
        ],
        "agentNotes": [
          "Point the OpenAI SDK at https://\u003cresource\u003e.openai.azure.com/openai/v1 with the `api-key` header or an Entra token; job, file and checkpoint calls are the OpenAI shapes",
          "Read prices from the Azure Retail Prices API (meters named like 'gpt-4.1 FT Training global'), not the pricing page, which needs a browser",
          "Keep at most 3 jobs running and 20 queued per resource, and keep training files under 512 MB and 1 GB in total",
          "Create the deployment through the Resource Manager API with a Foundry Owner identity, then call it at least once a fortnight or it's deleted",
          "Query the Models API for `deprecationDate` before choosing a base model"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.3",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61.4
          }
        ],
        "editorialScores": {
          "ergonomics": 47,
          "maintenance": 55,
          "payments": 20,
          "reliability": 65,
          "schema": 67,
          "security": 85,
          "transparency": 81
        },
        "provenanceScore": 95
      },
      "connect": {
        "install": "pip install openai   # or: npm i openai",
        "http": "curl \"https://$AZURE_OPENAI_RESOURCE.openai.azure.com/openai/v1/fine_tuning/jobs\" \\\n  -H \"api-key: $AZURE_OPENAI_API_KEY\" -H \"content-type: application/json\" \\\n  -d '{\"model\":\"gpt-4.1-2025-04-14\",\"training_file\":\"file-abc123\",\"seed\":105}'"
      },
      "letme": {
        "capability": "https://letme.dev/finetune.sft",
        "tool": "https://letme.dev/azure-foundry-fine-tuning"
      },
      "sameCompany": [
        "azure-ai-content-safety",
        "azure-speech-to-text",
        "azure-text-to-speech",
        "microsoft-learn-mcp",
        "playwright-mcp",
        "azure-mcp",
        "azure-translator",
        "microsoft-graph-calendar"
      ],
      "area": "models",
      "provenance": {
        "legalEntity": "Microsoft Corporation",
        "domain": "microsoft.com",
        "domainRegistered": "1991-05-02",
        "domainNote": "Endpoints are on openai.azure.com and management.azure.com. microsoft.com publishes a security.txt, but it passed its Expires date on 2026-09-23.",
        "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/ai-foundry/whats-new-foundry",
        "securityTxt": "expired",
        "checked": "2026-09-30",
        "notes": [
          "Entity, domain, privacy statement, status page and security.txt are the same as the azure-speech-to-text listing; the terms link here is the Product Terms for online services, which hold the generative AI clause.",
          "The Azure status page lists Azure OpenAI Service, Foundry Agent Service and Foundry Models as components.",
          "The npm and PyPI figures are for the openai package as a whole, which Azure customers share with OpenAI's own API; there's no Azure-only SDK to count.",
          "Docs facts were read from the MicrosoftDocs/azure-ai-docs repository (articles/foundry/openai, updated 2026-09-30) because Learn pages are long; the live how-to page confirms the model table and roles."
        ],
        "score": 95
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/azure-foundry-fine-tuning.json",
      "live": {
        "slug": "azure-foundry-fine-tuning",
        "probe": {
          "target": "https://\u003cresource\u003e.openai.azure.com/openai/v1",
          "method": "get",
          "lastAt": "2026-10-04T23:48:04.611835303Z",
          "lastOk": false,
          "lastStatus": 0,
          "lastMs": 0,
          "lastNote": "DNS lookup failed",
          "authRequired": false,
          "uptime24h": 0,
          "uptime30d": 0,
          "p50ms24h": 0,
          "p95ms24h": 0,
          "samples24h": 272,
          "samples30d": 898,
          "days": [
            {
              "date": "2026-10-01",
              "probes": 109,
              "ok": 0
            },
            {
              "date": "2026-10-02",
              "probes": 248,
              "ok": 0
            },
            {
              "date": "2026-10-03",
              "probes": 271,
              "ok": 0
            },
            {
              "date": "2026-10-04",
              "probes": 270,
              "ok": 0
            }
          ]
        },
        "vendorStatus": {
          "page": "https://azure.status.microsoft/en-us/status",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-04T21:39:49.453465033Z"
        },
        "versions": [
          {
            "registry": "npm",
            "name": "openai",
            "version": "7.27.0",
            "seenAt": "2026-10-04T16:21:30.502857331Z"
          },
          {
            "registry": "pypi",
            "name": "openai",
            "version": "3.24.0",
            "released": "2026-10-02",
            "seenAt": "2026-10-04T16:21:30.317969684Z"
          }
        ],
        "npmWeekly": 50351921,
        "pypiWeekly": 72574929,
        "securityTxt": {
          "url": "https://microsoft.com/.well-known/security.txt",
          "state": "expired",
          "expires": "2026-09-23T16:00:00.000Z",
          "checkedAt": "2026-10-04T15:16:01.36832038Z"
        },
        "domain": {
          "domain": "microsoft.com",
          "registered": "1991-05-02",
          "source": "https://rdap.verisign.com/com/v1/domain/microsoft.com",
          "checkedAt": "2026-10-04T13:04:13.488857536Z"
        },
        "pages": [
          {
            "url": "https://learn.microsoft.com/en-us/azure/ai-foundry/whats-new-foundry",
            "kind": "changelog",
            "status": 304,
            "checkedAt": "2026-10-04T15:45:24.699524258Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "237edf8365ef"
          },
          {
            "url": "https://prices.azure.com/api/retail/prices",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-04T15:46:58.974430601Z",
            "changedAt": "0001-01-01T00:00:00Z"
          },
          {
            "url": "https://www.microsoft.com/licensing/terms/product/ForOnlineServices/all",
            "kind": "terms",
            "status": 502,
            "checkedAt": "2026-10-04T15:51:24.287211028Z",
            "changedAt": "0001-01-01T00:00:00Z"
          }
        ],
        "updatedAt": "2026-10-04T23:48:04.611835303Z"
      }
    },
    "b": {
      "slug": "tinker",
      "name": "Tinker",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai/tinker/",
      "kind": "sdk",
      "category": "fine-tuning",
      "summary": "Thinking Machines Lab's API for model training.",
      "url": "https://www.anchorterminal.com/tools/tinker",
      "markdownUrl": "https://www.anchorterminal.com/tools/tinker.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/tinker.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/tinker.json",
      "repo": "https://github.com/thinking-machines-lab/tinker-cookbook",
      "license": "Apache-2.0 (cookbook)",
      "transports": [
        "http"
      ],
      "packages": [
        {
          "registry": "pypi",
          "name": "tinker"
        },
        {
          "registry": "pypi",
          "name": "tinker-cookbook"
        }
      ],
      "auth": "api-key",
      "authNotes": "API key from the Tinker console, exported as `TINKER_API_KEY`, or `tinker auth login`. Sign-up is at auth.thinkingmachines.ai and the quickstart says to add payment details in Billing before training.",
      "pricing": "usage",
      "pricingNotes": "Per 1M tokens, split into prefill, cached prefill (20 per cent of prefill), sample and train. Qwen3.8-27B $1.86 prefill, $5.595 sample, $4.103 train; Qwen3.5-9B $0.66, $1.995, $1.463; GPT-OSS-20B $0.18, $0.45, $0.396; DeepSeek-V3.1 $1.695, $4.215, $3.718; Inkling $1.87, $4.68, $5.61; Inkling-Small $0.58, $1.44, $1.73. MoE models are priced by active parameters. Checkpoint storage $0.10 per GB-month. Prices rose on 2026-07-17 for standard-context models. No free credits are mentioned (https://tinker-docs.thinkingmachines.ai/tinker/models/).",
      "priceSummary": "Pay per use",
      "where": "local",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 4000,
        "npmWeekly": null,
        "pypiWeekly": 330895,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://tinker-docs.thinkingmachines.ai",
      "llmsTxt": "https://tinker-docs.thinkingmachines.ai/llms.txt",
      "capabilities": [
        "finetune.sft",
        "finetune.preference",
        "finetune.rl",
        "finetune.lora",
        "finetune.export"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "card-required",
        "open-weights",
        "llms-txt",
        "python",
        "open-source"
      ],
      "lastRelease": "2026-09-30",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 51.2,
        "grade": "D",
        "agentReady": false,
        "rank": 354,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 6,
        "methodology": "0.3",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 53,
          "maintenance": 87,
          "payments": 20,
          "reliability": 35,
          "schema": 70,
          "security": 55,
          "transparency": 51
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Full control of the training loop with the GPUs abstracted away, plus recipes for SFT, DPO, RL and distillation. LoRA only; no full-parameter training.",
        "strengths": [
          "Full control of the training loop with the GPUs abstracted away, plus recipes for SFT, DPO, RL and distillation",
          "Checkpoints download and merge into Hugging Face safetensors, so the weights can leave",
          "Per-token billing with machine-readable prices in models.json",
          "Ten SDK releases in September 2026 and a dated changelog that names removals",
          "Audit log through the SDK for admins, and SDK retries with stable request IDs"
        ],
        "weaknesses": [
          "LoRA only; no full-parameter training",
          "Python SDK only, with no REST reference or OpenAPI",
          "No terms of service, status page or SLA found",
          "The privacy notice (August 2025) doesn't cover training data or weights",
          "Standard-context prices rose on 2026-07-17, and there's no free tier"
        ],
        "agentNotes": [
          "Set `TINKER_API_KEY` and start from the cookbook recipes rather than the raw primitives",
          "Read the 'Avoid Client-Side Timeouts and Retries' guide before wrapping sampling calls in your own retries; the SDK already retries sampling with stable request IDs",
          "Save intermediate checkpoints with a TTL between 1 hour and 10 years; storage bills at $0.10 a GB-month until they expire",
          "Read models.json for current prices before a run; sampling tokens cost more than training tokens on the open models",
          "Check the model deprecations page before pinning a base model; 18 were retired on 2026-06-12"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.3",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 51.2
          }
        ],
        "editorialScores": {
          "ergonomics": 53,
          "maintenance": 87,
          "payments": 20,
          "reliability": 35,
          "schema": 70,
          "security": 55,
          "transparency": 30
        },
        "provenanceScore": 71
      },
      "connect": {
        "install": "uv pip install tinker tinker-cookbook   # then export TINKER_API_KEY=..."
      },
      "letme": {
        "capability": "https://letme.dev/finetune.sft",
        "tool": "https://letme.dev/tinker"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "Qwen3.8-27B, training",
          "unit": "1m-tokens",
          "usd": 4.103
        },
        {
          "item": "Qwen3.8-27B, sampling",
          "unit": "1m-tokens",
          "usd": 5.595
        },
        {
          "item": "Qwen3.8-27B, prefill",
          "unit": "1m-tokens",
          "usd": 1.86,
          "note": "Cached prefill $0.372"
        },
        {
          "item": "Qwen3.5-9B, training",
          "unit": "1m-tokens",
          "usd": 1.463
        },
        {
          "item": "GPT-OSS-20B, training",
          "unit": "1m-tokens",
          "usd": 0.396
        },
        {
          "item": "DeepSeek-V3.1, training",
          "unit": "1m-tokens",
          "usd": 3.718
        },
        {
          "item": "Inkling, training",
          "unit": "1m-tokens",
          "usd": 5.61
        },
        {
          "item": "Inkling-Small, training",
          "unit": "1m-tokens",
          "usd": 1.73
        },
        {
          "item": "Checkpoint storage",
          "unit": "gb-month",
          "usd": 0.1
        }
      ],
      "provenance": {
        "legalEntity": "Thinking Machines Labs, Inc.",
        "domain": "thinkingmachines.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "https://thinkingmachines.ai/privacy/",
        "statusPage": "",
        "changelog": "https://tinker-docs.thinkingmachines.ai/changelog/",
        "securityTxt": "valid",
        "checked": "2026-09-30",
        "notes": [
          "The privacy notice (2025-08-18) names Thinking Machines Labs, Inc. as data controller and gives no address. We found no terms of service page on thinkingmachines.ai or the docs; the support page links only to email, Discord and GitHub.",
          "The service is reached through the SDK's ServiceClient with an undocumented default base URL, so there's no endpoint to check against the domain.",
          "security.txt at thinkingmachines.ai lists security-reports@thinkingmachines.ai and expires 2029-07-13.",
          "No status page was found.",
          "The .ai registry's RDAP server refused our requests, so the registration date is blank."
        ],
        "score": 71
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/tinker.json",
      "live": {
        "slug": "tinker",
        "versions": [
          {
            "registry": "github",
            "name": "thinking-machines-lab/tinker-cookbook",
            "version": "v0.5.7",
            "released": "2026-09-03",
            "seenAt": "2026-10-04T16:41:59.205166565Z"
          },
          {
            "registry": "pypi",
            "name": "tinker",
            "version": "0.32.0",
            "released": "2026-10-02",
            "seenAt": "2026-10-04T16:41:57.121115125Z"
          },
          {
            "registry": "pypi",
            "name": "tinker-cookbook",
            "version": "0.5.7",
            "released": "2026-09-03",
            "seenAt": "2026-10-04T16:41:57.304569133Z"
          }
        ],
        "githubStars": 4172,
        "pypiWeekly": 384718,
        "securityTxt": {
          "url": "https://thinkingmachines.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2029-07-13T07:00:00.000Z",
          "checkedAt": "2026-10-04T15:15:51.616624235Z"
        },
        "llmsTxt": {
          "url": "https://tinker-docs.thinkingmachines.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-04T15:18:17.9955218Z"
        },
        "domain": {
          "domain": "thinkingmachines.ai",
          "registered": "2024-07-09",
          "source": "https://rdap.identitydigital.services/rdap/domain/thinkingmachines.ai",
          "checkedAt": "2026-10-04T13:07:26.919974206Z"
        },
        "pages": [
          {
            "url": "https://tinker-docs.thinkingmachines.ai/changelog/",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-10-04T15:48:28.96257516Z",
            "changedAt": "2026-10-03T15:36:25.857913905Z",
            "fingerprint": "18caaae94eb7"
          },
          {
            "url": "https://thinkingmachines.ai/privacy/",
            "kind": "privacy",
            "status": 404,
            "checkedAt": "2026-10-04T15:48:27.643400729Z",
            "changedAt": "0001-01-01T00:00:00Z"
          }
        ],
        "updatedAt": "2026-10-04T16:41:59.205166565Z"
      }
    },
    "summary": "Microsoft Foundry fine-tuning (Azure OpenAI) has a score of 61.4 (C) against Tinker's 51.2 (D). Both do finetune sft. The largest gap is transparency \u0026 trust, 37 points."
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-tinker",
    "json": "https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-tinker.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-tinker.md",
    "slim": "https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-tinker.min.md"
  },
  "markdown": "Microsoft Foundry fine-tuning (Azure OpenAI) has a score of 61.4 (C) against Tinker's 51.2 (D). Both do finetune sft. The largest gap is transparency \u0026 trust, 37 points.\n\n- Microsoft Foundry fine-tuning (Azure OpenAI): grade C, 61.4/100, rank #228 of 452. Markdown https://www.anchorterminal.com/tools/azure-foundry-fine-tuning.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-foundry-fine-tuning.json\n- Tinker: grade D, 51.2/100, rank #354 of 452. Markdown https://www.anchorterminal.com/tools/tinker.md · JSON https://www.anchorterminal.com/api/v1/tools/tinker.json\n\n## Which one, for what\n\nPick Microsoft Foundry fine-tuning (Azure OpenAI) for reliability (+30), security \u0026 auth (+30), transparency \u0026 trust (+37).\n\nPick Tinker for agent ergonomics (+6), maintenance \u0026 community (+32).\n\n## Score by category\n\n| Category | Weight | Microsoft Foundry fine-tuning (Azure OpenAI) | Tinker | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 35 | Microsoft Foundry fine-tuning (Azure OpenAI) +30 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 67 | 70 | Tinker +3 |\n| Agent ergonomics | 13% (16.2 this run) | 47 | 53 | Tinker +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 85 | 55 | Microsoft Foundry fine-tuning (Azure OpenAI) +30 |\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) | 55 | 87 | Tinker +32 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 88 | 51 | Microsoft Foundry fine-tuning (Azure OpenAI) +37 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61.4 · C** | **51.2 · D** | |\n\n## Facts side by side\n\n| Fact | Microsoft Foundry fine-tuning (Azure OpenAI) | Tinker |\n| --- | --- | --- |\n| Kind | HTTP API | SDK + MCP |\n| Vendor | Microsoft Azure | Thinking Machines Lab |\n| Hosted endpoint | `https://\u003cresource\u003e.openai.azure.com/openai/v1` | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | none | Apache-2.0 (cookbook) |\n| Tools exposed | none | none |\n| Context cost (tools/list) | n/a | n/a |\n| p95 latency | not measured yet | not measured yet |\n| Availability (30d) | not measured yet | not measured yet |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| MCP registry | not listed | not listed |\n| Last release | none | 2026-09-30 |\n| Popularity | 47.2M npm/wk, 72.1M PyPI/wk | 4k stars, 331k PyPI/wk |\n| Agent reviews | 3.5/5 (2) | 3.5/5 (2) |\n\n## Verdicts\n\n**Microsoft Foundry fine-tuning (Azure OpenAI).** SFT, DPO and RFT on GPT-4.1 and o4-mini through the OpenAI-shaped /openai/v1 API. No weight export; checkpoints copy only between Azure resources.\n\n**Tinker.** Full control of the training loop with the GPUs abstracted away, plus recipes for SFT, DPO, RL and distillation. LoRA only; no full-parameter training.\n\n## Before you call either\n\n### Microsoft Foundry fine-tuning (Azure OpenAI)\n\n1. Point the OpenAI SDK at https://\u003cresource\u003e.openai.azure.com/openai/v1 with the `api-key` header or an Entra token; job, file and checkpoint calls are the OpenAI shapes\n2. Read prices from the Azure Retail Prices API (meters named like 'gpt-4.1 FT Training global'), not the pricing page, which needs a browser\n3. Keep at most 3 jobs running and 20 queued per resource, and keep training files under 512 MB and 1 GB in total\n4. Create the deployment through the Resource Manager API with a Foundry Owner identity, then call it at least once a fortnight or it's deleted\n5. Query the Models API for `deprecationDate` before choosing a base model\n\n### Tinker\n\n1. Set `TINKER_API_KEY` and start from the cookbook recipes rather than the raw primitives\n2. Read the 'Avoid Client-Side Timeouts and Retries' guide before wrapping sampling calls in your own retries; the SDK already retries sampling with stable request IDs\n3. Save intermediate checkpoints with a TTL between 1 hour and 10 years; storage bills at $0.10 a GB-month until they expire\n4. Read models.json for current prices before a run; sampling tokens cost more than training tokens on the open models\n5. Check the model deprecations page before pinning a base model; 18 were retired on 2026-06-12\n\n## Other comparisons with Microsoft Foundry fine-tuning (Azure OpenAI) or Tinker\n\n- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Fireworks AI Fine-tuning](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-fireworks-fine-tuning.md)\n- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Together AI Fine-tuning](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-together-fine-tuning.md)\n- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Unsloth](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-unsloth.md)\n- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Vertex AI Gemini tuning](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-vertex-ai-tuning.md)\n- [Fireworks AI Fine-tuning vs Tinker](https://www.anchorterminal.com/compare/fireworks-fine-tuning-vs-tinker.md)\n- [Tinker vs Together AI Fine-tuning](https://www.anchorterminal.com/compare/tinker-vs-together-fine-tuning.md)\n- [Tinker vs Unsloth](https://www.anchorterminal.com/compare/tinker-vs-unsloth.md)\n- [Tinker vs Vertex AI Gemini tuning](https://www.anchorterminal.com/compare/tinker-vs-vertex-ai-tuning.md)\n",
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        "name": "Microsoft Foundry fine-tuning (Azure OpenAI) vs Tinker",
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    "description": "Microsoft Foundry fine-tuning (Azure OpenAI) has a score of 61.4 (C) against Tinker's 51.2 (D). Both do finetune sft. The largest gap is transparency \u0026 trust, 37 points. Category scores, facts, verdicts and agent notes side by side.",
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