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articles/ai-services/openai/concepts/model-retirements.md

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description: Learn about the model deprecations and retirements in Azure OpenAI.
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ms.service: azure-ai-openai
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ms.topic: conceptual
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ms.date: 04/17/2025
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ms.date: 04/23/2025
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ms.custom:
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manager: nitinme
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author: mrbullwinkle
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| ---- | ---- | ---- | --- |
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| `dall-e-3` | 3 | No earlier than June 30, 2025 | |
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| `gpt-35-turbo-16k`| 0613 | April, 30, 2025 | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini`|
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| `gpt-35-turbo` | 1106 | No earlier than May 31, 2025 <br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on January 21, 2025. | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini` |
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| `gpt-35-turbo` | 0125 | No earlier than May 31, 2025 | `gpt-4o-mini` |
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| `gpt-35-turbo` | 1106 | July 16, 2025 <br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on January 21, 2025. | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini` |
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| `gpt-35-turbo` | 0125 | July 16, 2025 | `gpt-4o-mini` |
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| `gpt-4`<br>`gpt-4-32k` | 0314 | June 6, 2025 | `gpt-4o` |
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| `gpt-4`<br>`gpt-4-32k` | 0613 | June 6, 2025 | `gpt-4o` |
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| `gpt-4` | turbo-2024-04-09 | No earlier than June 6, 2025 | `gpt-4o`|
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| `gpt-4` | 1106-preview | To be upgraded to **`gpt-4o` version: `2024-11-20`**, starting no sooner than April 17, 2025 **<sup>1</sup>** <br>Retirement date: May 1, 2025 | `gpt-4o`|
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| `gpt-4` | 0125-preview |To be upgraded to **`gpt-4o` version: `2024-11-20`**, starting no sooner than April 17, 2025 **<sup>1</sup>** <br>Retirement date: May 1, 2025 | `gpt-4o` |
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| `gpt-4` | vision-preview | To be upgraded to **`gpt-4o` version: `2024-11-20`**, starting no sooner than April 17, 2025 **<sup>1</sup>** <br>Retirement date: May 1, 2025 | `gpt-4o`|
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| `gpt-4` | vision-preview | To be upgraded to **`gpt-4o` version: `2024-11-20`**, starting no sooner than April 17, 2025 **<sup>1</sup>** <br>Retirement date: May 15, 2025 | `gpt-4o`|
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| `gpt-4.5-preview` | 2025-02-27 | July 14, 2025 | `gpt-4.1` |
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| `gpt-4.1` | 2025-04-14 | No earlier than April 11, 2026 | |
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| `gpt-4.1-mini` | 2025-04-14 | No earlier than April 11, 2026 |
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| `gpt-4.1-nano` | 2025-04-14 | No earlier than April 11, 2026 |
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| `gpt-4o` | 2024-05-13 | No earlier than June 30, 2025 <br><br>Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `2024-08-06`, starting on March 17, 2025. | |
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| `gpt-4o` | 2024-08-06 | No earlier than August 6, 2025 | |
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| `gpt-4o` | 2024-11-20 | No earlier than November 20, 2025 | |
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| `gpt-4o-mini` | 2024-07-18 | No earlier than July 18, 2025 | |
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| `gpt-4o` | 2024-11-20 | January 30, 2026 | |
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| `gpt-4o-mini` | 2024-07-18 | August 16, 2025 | |
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| `gpt-4o-realtime-preview` | 2024-10-01 | **Deprecated:** February 25, 2025<br>**Retirement:** No earlier than March 26, 2025 | `gpt-4o-realtime-preview` (version 2024-12-17) or `gpt-4o-mini-realtime-preview` (version 2024-12-17) |
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| `gpt-3.5-turbo-instruct` | 0914 | No earlier than May 31, 2025 | |
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| `o1-preview` | 2024-09-12 | No earlier than April 2, 2025 | `o1` |
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| `o1-preview` | 2024-09-12 | May 29, 2025 | `o1` |
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| `o1` | 2024-12-17 | No earlier than December 17, 2025 | |
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| `o4-mini` | 2025-04-16 | No earlier than April 11, 2026 | |
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| `o3` | 2025-04-16 | No earlier than April 11, 2026 | |

articles/ai-services/openai/how-to/evaluations.md

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ROUGE (Recall-Oriented Understudy for Gisting Evaluation) is a set of metrics used to evaluate automatic summarization and machine translation. It measures the overlap between generated text and reference summaries. ROUGE focuses on recall-oriented measures to assess how well the generated text covers the reference text.
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The ROUGE score provides various metrics, including:
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• ROUGE-1: Overlap of unigrams (single words) between generated and reference text.
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• ROUGE-2: Overlap of bigrams (two consecutive words) between generated and reference text.
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• ROUGE-3: Overlap of trigrams (three consecutive words) between generated and reference text.
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• ROUGE-4: Overlap of four-grams (four consecutive words) between generated and reference text.
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• ROUGE-5: Overlap of five-grams (five consecutive words) between generated and reference text.
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• ROUGE-L: Overlap of L-grams (L consecutive words) between generated and reference text.
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- ROUGE-1: Overlap of unigrams (single words) between generated and reference text.
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- ROUGE-2: Overlap of bigrams (two consecutive words) between generated and reference text.
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- ROUGE-3: Overlap of trigrams (three consecutive words) between generated and reference text.
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- ROUGE-4: Overlap of four-grams (four consecutive words) between generated and reference text.
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- ROUGE-5: Overlap of five-grams (five consecutive words) between generated and reference text.
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- ROUGE-L: Overlap of L-grams (L consecutive words) between generated and reference text.
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Text summarization and document comparison are among optimal use cases for ROUGE, particularly in scenarios where text coherence and relevance are critical.
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Cosine similarity measures how closely two text embeddings—such as model outputs and reference texts—align in meaning, helping assess the semantic similarity between them. Same as other model-based evaluators, you need to provide a model deployment using for evaluation.

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