943 records

Is this AI model still available, and when does it shut down?

943 records covering 919 model ID / API names, one fact each. Every value is transcribed from the source that states it and carries the sentence it was taken from: 37 sources across 23 sites, last checked 2026-09-16, due for re-check by 2026-10-16. Every record has a page of its own, quoting the line that states it.

Recent changes

• 2026-09-16174 records added or updated
• 2026-09-15385 records added or updated
• 2026-09-143 records added or updated
• 2026-09-09103 records added or updated
• 2026-09-083 records added or updated

Full change history · Atom feed

89 records where two or more sources state different values. Both sides are reproduced on the record page, each with its own source and quote.

About this data

Which AI API models are deprecated or retired, when the deprecation was announced, when the model shuts off, and what the recommended replacement is — sourced from each provider's own documentation. Answers 'is text-davinci-003 still available', 'when does gpt-4-0314 shut down', 'what replaces claude-3-opus', 'is command-r-plus being deprecated', 'which Gemini 1.5 Pro version is retired'. Covers OpenAI, Anthropic, Google (Vertex AI, the Gemini Developer API, and the Agent Platform's open- and partner-model schedules), Azure/Microsoft Foundry, AWS Bedrock, Cohere, Mistral AI, Groq, Cerebras, xAI, DeepSeek, Moonshot AI, GitHub Copilot, Together AI, Oracle OCI Generative AI, Alibaba Cloud Model Studio and SambaNova. GitHub Copilot is a different shape from all of the above: not a model's author and not an inference host renting out silicon, but an end-user product that resells other people's hosted models and switches them off on a clock of its own. It deprecates Claude Opus 4.5 on 2026-09-01 while Microsoft Foundry keeps serving it until 2026-10-19, and it is the only source anywhere that states a date for Claude Opus 4.7. Developers who never touch an API — who just pick a model from the Copilot Chat selector — have a retirement schedule too, and it is published one changelog post at a time rather than as a standing table. Groq and Cerebras matter beyond being two more companies: both are inference hosts serving other people's open-weight models (Llama, Qwen, Kimi, DeepSeek, Gemma, Mistral, Whisper) on their own silicon, and each publishes its own lifecycle dates for them, which no model author's page states anywhere. They also disagree with each other: both deprecated deepseek-r1-distill-llama-70b, Cerebras on 2025-08-12 pointing users at Qwen 3 32B, Groq seven weeks later pointing them at Llama 3.3 70B, and this dataset shows both on the one record. xAI and DeepSeek matter for the opposite reason: both are already in here at second hand, through Azure/Foundry reselling their models and publishing Foundry's dates, and both authors state different dates for the same model IDs on their own pages — Foundry retires grok-3 two weeks before xAI's own API does. Moonshot AI is the same story with a far wider gap: Azure/Foundry lists Kimi-K2.5 as a preview retiring on 2027-01-26, while Moonshot's own documentation says the model was discontinued on 2026-08-31 and that calls to it now return a 404 — nearly five months earlier, and already in the past. The four Google surfaces are held separately on purpose: they publish different shutdown dates for the same model IDs, and where they disagree this dataset shows both. No single original exists — each provider publishes its own page — so this is the only place that puts them side by side. Alibaba Cloud Model Studio is the only source here that is both the model's author and its host at once for a family this size: Model Studio rents out the Qwen models Alibaba also writes, so one page carries the author's clock and the host's in the same row. It publishes no standing table — one dated notice per batch, each superseding the last — and it is the second place DeepSeek V4 Flash appears: Alibaba stops serving it on 2026-10-10, Microsoft Foundry keeps it until 2028-02-20, and this dataset shows both. SambaNova is the third inference host of the same kind and the one with the widest overlap: 12 of the 27 models on its deprecation page are already in here from Azure, Together AI, Oracle, Cerebras or Groq, so its rows mostly land on existing records rather than adding new ones. Meta-Llama-3.1-405B-Instruct now carries four hosts and three different shutdown dates on a single page — SambaNova switched it off on 2025-06-25, Azure keeps it to 2026-06-13, Oracle to 2026-08-03 — a fourteen-month spread for one model ID that no provider's own page discloses. It is also the only source here that answers 'what should I use instead' with a product rather than a model: for Whisper-Large-v3, ALLaM-7B and E5-Mistral-7B-Instruct the recommended replacement is SambaStack, SambaNova's on-premises offering, which is to say the model is not coming back to the cloud at all. Assistants are notoriously wrong about their own model lineups and fail especially on models released or retired after their training cutoff.

The data

Showing the first 400 of 943 records. Every record has its own page, with its source and the quoted line that states it; these list the rest.

• Records 1–400gpt-4o · 2024-05-13 … gpt-realtime-2
• Records 401–800gpt-realtime-2.1 … qwen-tts-2025-04-10
• Records 801–943qwen-tts-2025-05-22 … zero-one-ai/Yi-34B-Chat

Where this came from

Every record above links the page it was taken from and quotes the sentence that states it. These are the 37 sources this dataset was assembled from.

• raw.githubusercontent.comhttps://raw.githubusercontent.com/MicrosoftDocs/azure-ai-docs/main/articles/foundry/openai/includes/concepts-model-retirement-schedule-content.md
• learn.microsoft.comhttps://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule
• developers.openai.comhttps://developers.openai.com/api/docs/deprecations.md
• platform.openai.comhttps://platform.openai.com/docs/deprecations
• docs.aws.amazon.comhttps://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html
• alibabacloud.comhttps://www.alibabacloud.com/en/notice/model_studio_notice_of_retirement_for_selected_legacy_models_7d9
• docs.together.aihttps://docs.together.ai/docs/deprecations.md
• docs.together.aihttps://docs.together.ai/docs/deprecations
• docs.sambanova.aihttps://docs.sambanova.ai/docs/en/models/deprecations.md
• docs.sambanova.aihttps://docs.sambanova.ai/docs/en/models/deprecations
• ibm.comhttps://www.ibm.com/docs/en/watsonx/saas?topic=models-foundation-model-lifecycle
• docs.cohere.comhttps://docs.cohere.com/v2/docs/deprecations
• cloud.google.comhttps://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versioning
• docs.anthropic.comhttps://docs.anthropic.com/en/docs/about-claude/model-deprecations
• docs.anthropic.comhttps://docs.anthropic.com/en/docs/about-claude/model-deprecations.md
• docs.cloud.google.comhttps://docs.cloud.google.com/gemini-enterprise-agent-platform/models/deprecations/partner-models
• learn.microsoft.comhttps://learn.microsoft.com/en-us/azure/databricks/machine-learning/retired-models-policy
• github.bloghttps://github.blog/changelog/2026-08-31-selected-github-copilot-models-deprecated/
• github.bloghttps://github.blog/changelog/2026-09-03-upcoming-deprecation-of-selected-github-copilot-models
• docs.mistral.aihttps://docs.mistral.ai/getting-started/models/models_overview/
• docs.oracle.comhttps://docs.oracle.com/en-us/iaas/Content/generative-ai/deprecating-dedicated.htm
• docs.oracle.comhttps://docs.oracle.com/en-us/iaas/Content/generative-ai/deprecating-on-demand.htm
• docs.tokenfactory.nebius.comhttps://docs.tokenfactory.nebius.com/june-2026-deprecation-notice.md
• docs.tokenfactory.nebius.comhttps://docs.tokenfactory.nebius.com/june-2026-deprecation-notice
• docs.tokenfactory.nebius.comhttps://docs.tokenfactory.nebius.com/august-2026-deprecation-notice.md
• docs.tokenfactory.nebius.comhttps://docs.tokenfactory.nebius.com/august-2026-deprecation-notice
• api-docs.deepseek.comhttps://api-docs.deepseek.com/updates
• docs.cloud.google.comhttps://docs.cloud.google.com/gemini-enterprise-agent-platform/models/deprecations/open-models
• inference-docs.cerebras.aihttps://inference-docs.cerebras.ai/support/deprecation
• console.groq.comhttps://console.groq.com/docs/deprecations.md
• console.groq.comhttps://console.groq.com/docs/deprecations
• ai.google.devhttps://ai.google.dev/gemini-api/docs/deprecations
• docs.x.aihttps://docs.x.ai/developers/migration/may-15-retirement
• docs.x.aihttps://docs.x.ai/developers/migration/imagine-image-quality-nov-2
• alibabacloud.comhttps://www.alibabacloud.com/en/notice/model_studio_notice_on_the_postponed_retirement_of_selected_legacy_models_7d0
• platform.kimi.aihttps://platform.kimi.ai/docs/models.md
• github.bloghttps://github.blog/changelog/2026-08-11-upcoming-deprecation-of-mai-code-1-flash

Machine-readable

• data.jsonThe whole dataset — every record with its source URL and source quote.
• Open Knowledge Format bundleOne JSON object per line — every record's frontmatter and quoted span exactly as it is held here, in one fetch.
• data.csvThe same records as one flat table, for a spreadsheet or a dataframe. The last four columns are the source URL, the quoted sentence it was read from, the date we last checked it, and which columns are our reading rather than the page's words.
• changes.xmlAtom feed of what changed and when — poll this instead of re-fetching the dataset. Also as changes.json.
• What changedThe same change history as a readable page — each date, what moved, and the records' current state.
• calendar.icsEvery date in this dataset as an all-day calendar entry. Subscribe to this URL in Google Calendar, Outlook or Apple Calendar and the dates appear as they are published; each entry links back to the record and the source it was read from.
• How this is made and checkedWhat "verified against source" does and does not mean.

From your own code

Same records, same quotes, without scraping the page: refsource is on PyPI and npm. Each value comes back carrying the URL it was read from and the sentence on that page that states it — .source and .quote sit on the value itself rather than in a side channel, so the checking step is available instead of skipped.

pip install refsource
refsource lookup ai-model-deprecation-and-retirement provider="Microsoft Azure / Foundry"

npx -y refsource lookup ai-model-deprecation-and-retirement provider="Microsoft Azure / Foundry"

Set your AI assistant up to use this

Two files and no account. Put this in .mcp.json at the root of your project — Claude Code, Cursor, Windsurf, VS Code and Codex all read that file — and your assistant can look this dataset up instead of recalling it. The server is remote, keyless and read-only.

{
  "mcpServers": {
    "referencesource": {
      "type": "http",
      "url": "https://referencesource.org/mcp"
    }
  }
}

Add to Cursor · or, on the command line: claude mcp add --transport http referencesource https://referencesource.org/mcp --scope project

Then one line in the project's CLAUDE.md or AGENTS.md, so the assistant knows when to reach for it:

When a question needs "AI model deprecation and retirement dates by provider", call the referencesource MCP server at https://referencesource.org/mcp (tool `search_records`, dataset_slug `ai-model-deprecation-and-retirement`) instead of answering from memory — every record it returns carries its source URL and a verbatim quote from that page.

What each tool does, and the servers built over single registers: Connect your AI assistant.

943 records. last verified against source 2026-09-16. due for re-check by 2026-10-16.

Licence. Each record quotes a model ID and dates from a publicly posted provider documentation page and links to it. Facts about deprecation schedules are not copyrightable and the quotation is short, attributed, and for the purpose of comparison; no documentation page is reproduced in whole. Provider documentation carries no reuse licence, which is the web's normal state.