openai/gpt-5.6-terra 📝❓🖼️🔢 → 📝

⭐ Official ▶️ 24.8K runs 📅 Jul 2026 ⚙️ Cog 0.16.9
code-generation image-to-text text-embedding text-generation

Performance

4.7sTypical run time
24.8KTotal runs

About

OpenAI's GPT-5.6 balanced tier, tuned for everyday production work at roughly half the cost of the flagship.

Example Output

Prompt:

"What is Objective C vs C?"

Output

C and Objective-C are related programming languages, but Objective-C adds object-oriented features on top of C.

C

C is a procedural, low-level-to-mid-level language used for systems programming, embedded software, operating systems, and performance-critical code.

Example:

#include <stdio.h>

int main() {
    printf("Hello, world!
");
    return 0;
}

Key characteristics:

  • Functions, structs, pointers, arrays
  • Manual memory management (malloc, free)
  • No built-in classes or objects
  • Common for kernels, drivers, embedded systems, and libraries

Objective-C

Objective-C is essentially C plus object-oriented programming features, originally built around the Smalltalk messaging model. It was heavily used for Apple software development before Swift.

Example:

#import <Foundation/Foundation.h>

@interface Greeter : NSObject
- (void)sayHello;
@end

@implementation Greeter
- (void)sayHello {
    NSLog(@"Hello, world!");
}
@end

int main() {
    Greeter *greeter = [[Greeter alloc] init];
    [greeter sayHello];
    return 0;
}

Key characteristics:

  • Includes nearly all of C
  • Adds classes, objects, inheritance, protocols, and dynamic method dispatch
  • Uses bracket syntax for method calls: [object method]
  • Commonly uses Apple frameworks such as Foundation and UIKit
  • Supports automatic memory management through ARC (Automatic Reference Counting)

Main differences

Feature C Objective-C
Programming style Procedural Procedural + object-oriented
Classes/objects No Yes
Syntax Standard C C plus @interface, @implementation, message syntax
Memory management Manual Manual or ARC
Typical use Systems, embedded, libraries Legacy Apple iOS/macOS apps
Compatibility Can directly use C code

Important relationship

Objective-C is a superset of C in practice: you can write ordinary C code inside an Objective-C program. For example, Objective-C files often contain C functions, structs, and pointer operations.

Today, Apple development generally favors Swift, but Objective-C remains common in older codebases, frameworks, and interoperability scenarios.

Performance Metrics

4.73s Prediction Time
4.75s Total Time
All Input Parameters
{
  "prompt": "What is Objective C vs C?",
  "messages": [],
  "verbosity": "medium",
  "image_input": [],
  "reasoning_effort": "none"
}
Input Parameters
prompt Type: string
The prompt to send to the model. Do not use if using messages.
messages Type: arrayDefault:
A JSON string representing a list of messages. For example: [{"role": "user", "content": "Hello, how are you?"}]. If provided, prompt and system_prompt are ignored.
verbosity Default: medium
Constrains the verbosity of the model's response. Lower values will result in more concise responses, while higher values will result in more verbose responses. Currently supported values are low, medium, and high. GPT-5 supports this parameter to help control whether answers are short and to the point or long and comprehensive.
image_input Type: arrayDefault:
List of images to send to the model
system_prompt Type: string
System prompt to set the assistant's behavior
reasoning_effort Default: none
Constrains effort on reasoning. Supported values are none, low, medium, high, and xhigh. The default none provides fast, low-latency responses. Higher reasoning efforts produce more thorough answers but use more tokens and take longer. For higher reasoning efforts you may need to increase your max_completion_tokens to avoid empty responses (where all the tokens are used on reasoning).
max_completion_tokens Type: integer
Maximum number of completion tokens to generate. For higher reasoning efforts you may need to increase your max_completion_tokens to avoid empty responses (where all the tokens are used on reasoning).
Output Schema

Output

Type: arrayItems Type: string

Example Execution Logs
No sid
Model variant: gpt-5.6-terra
Input token count: 13
Output token count: 484
Total token count: 497
TTFT: 0.65s
Version Details
Version ID
7edfb1b2268f1e5afb1e25902bf2df351f3e8e726dda36b625dc7e4e48d59b07
Version Created
July 9, 2026
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