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Copy file name to clipboardExpand all lines: content/code-security/how-tos/secure-at-scale/configure-organization-security/manage-usage-and-access/giving-org-access-private-registries.md
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@@ -85,6 +85,13 @@ Any private registries used by the build must also be accessible to the workflow
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{% data variables.product.prodname_dependabot %} can use any of the org-level private registries, as well as uses any private registries defined in the `dependabot.yml` file in the repo.
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For each update job, {% data variables.product.prodname_dependabot %} supplies credentials only for organization-level private registry types that apply to the job's package ecosystem. Depending on the ecosystem, the applicable registry types can include Git source credentials in addition to credentials for the ecosystem's package registry.
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> [!NOTE]
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> The number of applicable organization-level private registry credentials provided to any single update job is capped at 100 for performance reasons.
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For a multi-ecosystem group, {% data variables.product.prodname_dependabot %} runs a separate update job for each ecosystem and combines the results into one pull request. Each ecosystem's update job has its own 100-registry limit, just as it would if the ecosystems were configured as separate updates.
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{% data variables.product.prodname_dependabot %} cannot check for security or version updates for code stored in a private registry unless it can access the registry. If you do not configure access to the private registry, then {% data variables.product.prodname_dependabot %} cannot raise pull requests to update any of the dependencies stored in the registry.
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When you configure access to one or more private registries, {% data variables.product.prodname_dependabot %} can propose pull requests to upgrade a vulnerable dependency or to maintain a dependency, see [AUTOTITLE](/code-security/how-tos/secure-your-supply-chain/manage-your-dependency-security/configure-access-to-private-registries) and [AUTOTITLE](/code-security/how-tos/secure-your-supply-chain/manage-your-dependency-security/configure-private-registries).
Copy file name to clipboardExpand all lines: content/copilot/concepts/agents/code-review.md
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@@ -164,8 +164,8 @@ For full instructions, see [AUTOTITLE](/copilot/how-tos/copilot-on-github/set-up
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{% data variables.copilot.copilot_code-review_short %} supports multiple {% data variables.product.prodname_copilot_short %} review effort levels, so you can choose the level of thoroughness that matches the criticality of your code.
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***Lite**: Standard review. Provides fast, targeted feedback on common issues such as bugs, security vulnerabilities, and style inconsistencies (default).
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***Balanced**: Routes pull requests to a higher-reasoning model for longer analysis of complex logic, security-sensitive code, and cross-service changes. Balanced reviews use more {% data variables.product.prodname_ai_credits_short %}, and may consume marginally more {% data variables.product.prodname_actions %} minutes, than Lite reviews.
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***Lite**: Standard review. Provides fast, targeted feedback on common issues such as bugs, security vulnerabilities, and style inconsistencies.
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***Balanced**: Routes pull requests to a higher-reasoning model for longer analysis of complex logic, security-sensitive code, and cross-service changes (default). Balanced reviews use more {% data variables.product.prodname_ai_credits_short %}, and may consume marginally more {% data variables.product.prodname_actions %} minutes, than Lite reviews.
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Use Balanced for security-sensitive code, multi-service pull requests, or repositories with strict quality standards. Use Lite for routine changes where fast feedback is more important than exhaustive analysis.
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@@ -178,7 +178,7 @@ When {% data variables.product.prodname_copilot_short %} determines which review
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1. The requestor's {% data variables.product.prodname_copilot_short %} review effort. For a new pull request, the requestor is the author. When someone marks a draft ready for review, that person is the requestor.
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1. A {% data variables.product.prodname_copilot_short %} review effort set for the repository
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1. A {% data variables.product.prodname_copilot_short %} review effort set for the organization, or the repository owner's {% data variables.product.prodname_copilot_short %} review effort on a user-owned repository
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1. {% data variables.product.github %}'s built-in default, which is Lite. Some owners have Balanced as the built-in default.
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1. {% data variables.product.github %}'s built-in default, which is Balanced.
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After {% data variables.copilot.copilot_code-review_short %} reviews a pull request, the pull request overview comment shows the effort level used for each review run.
Copy file name to clipboardExpand all lines: content/copilot/how-tos/copilot-on-github/set-up-copilot/configure-code-review.md
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***Balanced**: Deeper analysis of complex logic, security-sensitive code, and cross-service changes.
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***Max**: Most thorough review. This option appears with a **Coming soon** label and is not available yet.
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To return to the built-in default, select the **Default** option at the top of the menu. Until you choose a specific level, the control shows the built-in default that applies to you, either **Default (Lite)** or**Default (Balanced)**.
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To return to the built-in default, select the **Default** option at the top of the menu. Until you choose a specific level, the control shows the built-in default,**Default (Balanced)**.
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Your {% data variables.product.prodname_copilot_short %} review effort is independent of **Automatic {% data variables.copilot.copilot_code-review_short %}**. Turning automatic review off does not clear your {% data variables.product.prodname_copilot_short %} review effort or stop it from applying to reviews you request manually.
Copy file name to clipboardExpand all lines: content/copilot/reference/ai-models/model-comparison.md
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| {% data variables.copilot.copilot_gpt_55 %} | Great at complex reasoning, code analysis, and technical decision-making. |
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| {% data variables.copilot.copilot_gpt_56_sol %} | The highest reasoning ceiling in the GPT-5.6 family. Best for complex reasoning over large codebases and demanding, long-running agentic work. |
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| {% data variables.copilot.copilot_claude_sonnet_46 %} | Reliable completions and smarter reasoning under pressure. |
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| {% data variables.copilot.copilot_claude_opus_47 %} | Anthropic’s most powerful model. Strong at deep reasoning over large, complex codebases. |
Copy file name to clipboardExpand all lines: content/copilot/reference/ai-models/model-hosting.md
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* {% data variables.copilot.copilot_claude_sonnet_46 %}
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* {% data variables.copilot.copilot_claude_sonnet_5 %}
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* {% data variables.copilot.copilot_claude_sonnet_55 %}
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* {% data variables.copilot.copilot_claude_opus_47 %}
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* {% data variables.copilot.copilot_claude_opus_48 %}
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* {% data variables.copilot.copilot_claude_opus_48_fast %}
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* {% data variables.copilot.copilot_claude_opus_5 %}
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Used for:
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* {% data variables.copilot.copilot_gemini_35_flash %}
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* {% data variables.copilot.copilot_gemini_36_flash %}
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* {% data variables.copilot.copilot_gemini_37_flash %}
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* {% data variables.copilot.copilot_gemini_38_flash %}
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Used for:
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* {% data variables.copilot.copilot_kimi_k27_code %}
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* {% data variables.copilot.copilot_kimi_k3 %}
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{% data variables.copilot.copilot_kimi_k27_code %} and {% data variables.copilot.copilot_kimi_k3 %} were developed by Moonshot AI. They are open-weight models that may be less aligned than other {% data variables.product.prodname_copilot_short %} models, with an elevated risk of geographic bias. Before you enable either model, review the [{% data variables.copilot.copilot_kimi_k27_code %} model card](https://huggingface.co/moonshotai/Kimi-K2.7-Code) or the [{% data variables.copilot.copilot_kimi_k3 %} model card](https://huggingface.co/moonshotai/Kimi-K3) and run your own evaluations before enabling.
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{% data variables.copilot.copilot_kimi_k27_code %} is hosted on Azure AI Foundry infrastructure managed by {% data variables.product.github %} and Microsoft.
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{% data variables.copilot.copilot_kimi_k3 %} was developed by Moonshot AI. It is an open-weight model that may be less aligned than other {% data variables.product.prodname_copilot_short %} models, with an elevated risk of geographic bias. Before you enable the model, review the [{% data variables.copilot.copilot_kimi_k3 %} model card](https://huggingface.co/moonshotai/Kimi-K3) and run your own evaluations.
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{% data variables.copilot.copilot_kimi_k3 %} is hosted by {% data variables.product.github %} on Fireworks AI.
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Both models are covered by zero data retention agreements with the hosting providers. Fireworks AI and Azure AI Foundry do not use prompts or completions to train models, and prompts and completions are not sent to Moonshot AI.
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{% data variables.copilot.copilot_kimi_k3 %} is covered by a zero data retention agreement with the hosting provider. Fireworks AI does not use prompts or completions to train models, and prompts and completions are not sent to Moonshot AI.
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{% data variables.product.github %} does not use {% data variables.copilot.copilot_business_short %} or {% data variables.copilot.copilot_enterprise_short %} customer data to train AI models. For individual subscribers—{% data variables.copilot.copilot_free_short %}, {% data variables.copilot.copilot_pro_short %}, {% data variables.copilot.copilot_pro_plus_short %}, and {% data variables.copilot.copilot_max_short %} users—{% data variables.product.github %} may use {% data variables.product.prodname_copilot_short %} interaction data, including prompts (inputs), suggestions (outputs), and code snippets generated during {% data variables.product.prodname_copilot_short %} sessions to train and improve AI models, in accordance with our [AUTOTITLE](/free-pro-team@latest/site-policy/privacy-policies/github-general-privacy-statement) and applicable user settings. Individual subscribers can opt out of having their data used for AI model training. To manage this setting, see [AUTOTITLE](/copilot/how-tos/manage-your-account/manage-policies#model-training-and-improvements).
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When using {% data variables.copilot.copilot_kimi_k27_code %} or {% data variables.copilot.copilot_kimi_k3 %}, input prompts and output completions continue to run through {% data variables.product.prodname_copilot %}'s content filters.
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When using {% data variables.copilot.copilot_kimi_k3 %}, input prompts and output completions continue to run through {% data variables.product.prodname_copilot %}'s content filters.
Copy file name to clipboardExpand all lines: content/copilot/reference/copilot-billing/models-and-pricing.md
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{% data variables.copilot.copilot_pro_short %} and {% data variables.copilot.copilot_pro_plus_short %} subscribers on **existing annual billing plans** using the **request-based billing** model have different model multipliers. See [AUTOTITLE](/copilot/reference/copilot-billing/request-based-billing-legacy/model-multipliers-for-annual-plans).
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[^gemini-flash-promo]: {% data variables.copilot.copilot_gemini_36_flash %}, {% data variables.copilot.copilot_gemini_37_flash %}, and {% data variables.copilot.copilot_gemini_38_flash %} are available at the promotional pricing of $0.75 per 1M input tokens, $0.075 per 1M cached input tokens, and $3.75 per 1M output tokens through December 31, 2026.
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[^gemini-flash-promo]: {% data variables.copilot.copilot_gemini_37_flash %} and {% data variables.copilot.copilot_gemini_38_flash %} are available at the promotional pricing of $0.75 per 1M input tokens, $0.075 per 1M cached input tokens, and $3.75 per 1M output tokens through December 31, 2026.
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