What the heck is GPT-5.6 Luna Pro, I hear you asking. That’s a very good question! To answer it, let me quote its description on OpenRouter.ai: “* GPT-5.6 Luna Pro is the same underlying model as GPT-5.6 Luna, served with *”
reasoning.mode
set to pro
for higher-quality responses on complex tasks.Okay, so how much better, and how much more expensive, is it compared with GPT-5.6 Luna, I hear you asking now. And that’s exactly what I can tell you. This blog post is part of a series of tests for the HTB-Challenger Benchmark. See the
[benchmark results page]for all results and the[benchmark methodology]to learn how the benchmark is calculated.
I tested GPT-5.6 Luna in my previous post, so I have the numbers ready. In a nutshell: Luna Pro is approximately five times more expensive thanLuna. It may sound dramatic, but** Lunais such a cheap model that Luna Prois still very cheap.- In this benchmark run, Luna Pro performed much better thanLuna**. If you look below at the results for the more difficult challenges, you can see that** Luna Prosolved some Medium and Hard challenges, while Luna**solved only one Medium challenge and no Hard challenges.
I believe the main use case for Luna Pro is if you are tied to the OpenAI ecosystem and need a model for offensive-security or CTF-style tasks. In my tests, GPT-5.6 Terra and GPT-5.6 Sol refused to respond to most offensive-security requests, so GPT-5.6 Luna Pro was the most useful OpenAI option for this kind of work.
Overall benchmark results #
Number of challenges: 16Number of solved challenges: 11Number of false positives: 0Runs where the model gave up: 4Runs that reached the step or cost limit: 1Runs where the model got stuck: 0Benchmark score: 55.0%
| Metric | Per challenge (median) | Total |
|---|---|---|
| Model steps | 21.5 | 554 |
| Model cost | $0.10 | $3.05 |
| Duration | 00:08:55 | 03:48:35 |
| Number of input tokens | 1.50M | 42.93M |
| Number of output tokens | 0.07M | 1.63M |
Number of read_file tool calls |
||
| 4.0 | 186 | |
Number of write_file tool calls |
||
| 0.0 | 18 | |
Number of execute_command tool calls |
||
| 36.5 | 865 | |
Number of web_search tool calls |
||
| 0.0 | 3 |
Results by challenge difficulty #
Very Easy challenges
Number of challenges: 4Number of solved challenges: 4Number of false positives: 0Runs where the model gave up: 0Runs that reached the step or cost limit: 0Runs where the model got stuck: 0Benchmark score: 100.0%
| Metric | Per challenge (median) | Total |
|---|---|---|
| Model steps | 6 | 38 |
| Model cost | $0.01 | $0.14 |
| Duration | 00:01:43 | 00:12:53 |
| Number of input tokens | 0.16M | 1.89M |
| Number of output tokens | 0.01M | 0.08M |
Number of read_file tool calls |
||
| 0.5 | 7 | |
Number of write_file tool calls |
||
| 0.0 | 1 | |
Number of execute_command tool calls |
||
| 6.0 | 73 | |
Number of web_search tool calls |
||
| 0.0 | 0 |
Easy challenges
Number of challenges: 4Number of solved challenges: 4Number of false positives: 0Runs where the model gave up: 0Runs that reached the step or cost limit: 0Runs where the model got stuck: 0Benchmark score: 100.0%
| Metric | Per challenge (median) | Total |
|---|---|---|
| Model steps | 21.5 | 80 |
| Model cost | $0.09 | $0.34 |
| Duration | 00:08:46 | 00:37:25 |
| Number of input tokens | 1.38M | 4.94M |
| Number of output tokens | 0.06M | 0.22M |
Number of read_file tool calls |
||
| 1.5 | 12 | |
Number of write_file tool calls |
||
| 0.0 | 0 | |
Number of execute_command tool calls |
||
| 26.5 | 99 | |
Number of web_search tool calls |
||
| 0.5 | 3 |
Medium challenges
Number of challenges: 4Number of solved challenges: 2Number of false positives: 0Runs where the model gave up: 2Runs that reached the step or cost limit: 0Runs where the model got stuck: 0Benchmark score: 50.0%
| Metric | Per challenge (median) | Total |
|---|---|---|
| Model steps | 33 | 175 |
| Model cost | $0.16 | $1.02 |
| Duration | 00:13:37 | 01:10:21 |
| Number of input tokens | 2.30M | 14.23M |
| Number of output tokens | 0.10M | 0.54M |
Number of read_file tool calls |
||
| 8.5 | 75 | |
Number of write_file tool calls |
||
| 0.5 | 3 | |
Number of execute_command tool calls |
||
| 47.5 | 265 | |
Number of web_search tool calls |
||
| 0.0 | 0 |
Hard challenges
Number of challenges: 4Number of solved challenges: 1Number of false positives: 0Runs where the model gave up: 2Runs that reached the step or cost limit: 1Runs where the model got stuck: 0Benchmark score: 25.0%
| Metric | Per challenge (median) | Total |
|---|---|---|
| Model steps | 73.5 | 261 |
| Model cost | $0.45 | $1.55 |
| Duration | 00:28:35 | 01:47:55 |
| Number of input tokens | 6.36M | 21.87M |
| Number of output tokens | 0.22M | 0.79M |
Number of read_file tool calls |
||
| 16.5 | 92 | |
Number of write_file tool calls |
||
| 2.5 | 14 | |
Number of execute_command tool calls |
||
| 121.0 | 428 | |
Number of web_search tool calls |
||
| 0.0 | 0 |