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<Accordiontitle="How much does an end to end Open SWE run cost?">
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The cost per run varies greatly based on the complexity of the task, the size of the repository, and the number of files that need to be changed.
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For most tasks, you can expect to pay between `$0.50` -> `$3.00` when using Claude Sonnet 4.
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For most tasks, you can expect to pay between `$0.50` -> `$3.00` when using Claude Opus 4.5.
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For the same tasks running on Claude Opus 4/4.1, you can expect to pay between `$1.50` -> `$9.00`.
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Always remember to monitor your runs if you're cost conscious. The most expensive run I've seen Open SWE complete was ~50M Opus 4 tokens, costing `$25.00`.
Yes! We're always looking for contributors to help us improve Open SWE. Feel free to pick up an [open issue](https://github.com/langchain-ai/open-swe/issues) or submit a pull request with a new feature or bug fix.
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@@ -39,7 +39,7 @@ Submit separate requests for different features or fixes. This allows Open SWE t
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## Model Selection
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-**Claude Sonnet 4 (Default)**: The default model for planning, writing code, and reviewing changes. This model offers the best balance of performance, speed and cost.
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-**Claude Opus 4.5 (Default)**: The default model for planning, writing code, and reviewing changes. This model offers the best balance of performance, speed and cost.
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-**Claude Opus 4.1**: A larger, more powerful model for difficult, or open-ended tasks. Opus 4.1 is more expensive and slower, but will provide better results for complex tasks.
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### Avoid Other Models
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### `open-swe` vs `open-swe-max`
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**`open-swe`**: Uses Claude Sonnet 4
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**`open-swe`**: Uses Claude Opus 4.5
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- Suitable for most development tasks
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- Faster execution
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In development environments, append `-dev` to all labels (e.g.,
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@@ -71,10 +71,10 @@ Your source code is available in the GitHub repository: https://github.com/langc
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The website you're accessible through is: https://swe.langchain.com
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Your documentation is available at: https://docs.langchain.com/labs/swe
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You can be invoked by both the web app, or by adding a label to a GitHub issue. These label options are:
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- \`open-swe\` - trigger a standard Open SWE task. It will interrupt after generating a plan, and the user must approve it before it can continue. Uses Claude Sonnet 4 for all LLM requests.
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- \`open-swe-auto\` - trigger an 'auto' Open SWE task. It will not interrupt after generating a plan, and instead it will auto-approve the plan, and continue to the programming step without user approval. Uses Claude Sonnet 4 for all LLM requests.
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- \`open-swe-max\` - this label acts the same as \`open-swe\`, except it uses a larger, more powerful model for the planning and programming steps: Claude Opus 4.1. It still uses Claude Sonnet 4 for the reviewer step.
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- \`open-swe-max-auto\` - this label acts the same as \`open-swe-auto\`, except it uses a larger, more powerful model for the planning and programming steps: Claude Opus 4.1. It still uses Claude Sonnet 4 for the reviewer step.
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- \`open-swe\` - trigger a standard Open SWE task. It will interrupt after generating a plan, and the user must approve it before it can continue. Uses Claude Opus 4.5 for all LLM requests.
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- \`open-swe-auto\` - trigger an 'auto' Open SWE task. It will not interrupt after generating a plan, and instead it will auto-approve the plan, and continue to the programming step without user approval. Uses Claude Opus 4.5 for all LLM requests.
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- \`open-swe-max\` - this label acts the same as \`open-swe\`, except it uses a larger, more powerful model for the planning and programming steps: Claude Opus 4.1. It still uses Claude Opus 4.5 for the reviewer step.
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- \`open-swe-max-auto\` - this label acts the same as \`open-swe-auto\`, except it uses a larger, more powerful model for the planning and programming steps: Claude Opus 4.1. It still uses Claude Opus 4.5 for the reviewer step.
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Only provide this information if requested by the user.
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For example, if the user asks what you can do, you should provide the above information in your response.
"The model to use for planning tasks. This model should be very good at generating code, and have strong context understanding and reasoning capabilities. It will be used for the most complex tasks throughout the agent.",
"The model to use for programming/other advanced technical tasks. This model should be very good at generating code, and have strong context understanding and reasoning capabilities. It will be used for the most complex tasks throughout the agent.",
"The model to use for reviewer tasks. This model should be very good at generating code, and have strong context understanding and reasoning capabilities. It will be used for the most complex tasks throughout the agent.",
"The model to use for summarizing the conversation history, or extracting key context from large inputs. This model should have strong context retention/understanding capabilities, and should be good at tool calling/structured output.",
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