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Models
openai.gpt-6-solbedrock_mantle
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Context Length
1050K
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Max Output
1050K
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Input Cost
$2.20/M
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Output Cost
$11.00/M
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Mode
Responses
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Max Input Tokens
1050K
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Max Tokens
128K
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Supported Endpoints
/v1/chat/completions, /v1/responses
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Provider
Bedrock Mantle
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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 openai.gpt-6-sol?
Overview
- openai.gpt-6-sol is a responses model provided by Bedrock Mantle.
- This model offers an exceptional context window of 1050K tokens, making it ideal for processing extensive documents, long conversations, or large codebases.
Pricing
- Input processing costs $2.20 per million tokens.
- Output generation costs $11.00 per million tokens.
Output Capabilities
- The model can generate up to 1050K tokens in a single response.
Availability
- Available through the following endpoints: /v1/chat/completions, /v1/responses.
What capabilities does openai.gpt-6-sol 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.
- 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.
openai.gpt-6-sol Pricing Overview
At $2.20 per 1M input tokens and $11.00 per 1M output tokens, openai.gpt-6-sol ranks 94 out of 160 responses models by input cost. It is more expensive compared to the median of $2.00 for responses models, and is cheaper than 41% of models in this category.