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Models
gpt-5-pro-2025-10-06openai
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Context Length
128K
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Max Output
272K
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Input Cost
$15.00/M
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Output Cost
$120.00/M
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Mode
Responses
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Max Input Tokens
128K
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Max Tokens
272K
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Supported Endpoints
/v1/batch, /v1/responses
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Provider
OpenAI
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Tool Choice
Yes
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Response Schema
Yes
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Parallel Function Calling
Yes
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Prompt Caching
Yes
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System Messages
Yes
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Comparison Insights
Comprehensive analysis based on the latest model metadata from the comparison table above.
What should I know about gpt-5-pro-2025-10-06?
Overview
- gpt-5-pro-2025-10-06 is a responses model provided by OpenAI.
- With a context window of 128K tokens, this model can handle substantial inputs such as detailed documents or extended conversation histories.
Pricing
- Input processing costs $15.00 per million tokens.
- Output generation costs $120.00 per million tokens.
Output Capabilities
- The model can generate up to 272K tokens in a single response.
Availability
- Available through the following endpoints: /v1/batch, /v1/responses.
What capabilities does gpt-5-pro-2025-10-06 support?
- Supports function calling, enabling integration with external tools and APIs for extended functionality.
- Includes vision capabilities to process and analyze images alongside text inputs.
- Features advanced reasoning capabilities for complex problem-solving and multi-step logical tasks.
- Provides web search integration for accessing real-time information and current data.
- Allows explicit tool selection, giving developers fine-grained control over function execution.
- Supports structured response schemas for consistent, predictable output formatting.
- Enables parallel function calling to execute multiple operations simultaneously for improved efficiency.
- Implements prompt caching to reduce costs and latency for repeated or similar queries.
- Supports system messages for customizing model behavior and setting operational parameters.
gpt-5-pro-2025-10-06 Pricing Overview
At $15.00 per 1M input tokens and $120.00 per 1M output tokens, gpt-5-pro-2025-10-06 ranks 32 out of 50 responses models by input cost. It is more expensive compared to the median of $4.13 for responses models, and is cheaper than 36% of models in this category.