Compare codex-mini-latest with other models

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Models

codex-mini-latest

openai

Context Length

200K

Max Output

100K

Input Cost

$1.50/M

Output Cost

$6.00/M

Mode

Responses

Max Input Tokens

200K

Max Tokens

100K

Supported Endpoints

/v1/responses

Provider

OpenAI

Tool Choice

Yes

Response Schema

Yes

Parallel Function Calling

Yes

Prompt Caching

Yes

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 codex-mini-latest?

Overview

codex-mini-latest is a responses model provided by OpenAI.
With a context window of 200K tokens, this model can handle substantial inputs such as detailed documents or extended conversation histories.

Pricing

Input processing costs $1.50 per million tokens.
Output generation costs $6.00 per million tokens.

Output Capabilities

The model can generate up to 100K tokens in a single response.

Availability

Available through the following endpoints: /v1/responses.

What capabilities does codex-mini-latest 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.

codex-mini-latest Pricing Overview

At $1.50 per 1M input tokens and $6.00 per 1M output tokens, codex-mini-latest ranks 18 out of 50 responses models by input cost. It is more affordable compared to the median of $4.13 for responses models, and is cheaper than 64% of models in this category.