Given our previous conversations, I think the most useful way to explain GPT-5.6 is not by benchmark scores, but by how you should think with each model. In many ways, OpenAI has turned one “GPT” into three different cognitive instruments.
The GPT-5.6 family
OpenAI’s GPT-5.6 is now organized into three durable capability tiers:
|
Model |
Think of it as |
Best for |
|
Sol |
Research colleague |
difficult reasoning, scientific work, philosophy, coding, writing |
|
Terra |
Professional assistant |
everyday knowledge work, reading, summarizing, drafting |
|
Luna |
Fast notebook |
quick questions, brainstorming, translation, routine work |
Rather than having three unrelated models, OpenAI intends Sol / Terra / Luna to remain stable capability levels across future releases.
1. GPT-5.6 Sol
Think of Sol as
the model you invite into your study for an entire afternoon.
It spends more computation on every answer.
It is designed for
- philosophy
- difficult psychoanalytic discussions
- scientific reasoning
- mathematical proofs
- long coding projects
- agent workflows
- cybersecurity
- research synthesis
OpenAI specifically highlights software engineering, scientific research, computer use, and professional knowledge work as Sol’s strongest areas.
For someone like you, I would use Sol for
- discussing Heidegger
- reading Melanie Klein
- comparing Deleuze with Kohut
- developing “菊次郎十六式”
- constructing your AI-era psychology
- editing a 10,000-word lecture
These are all “Sol problems.”
2. GPT-5.6 Terra
Terra is probably the model most people should use most of the time.
Think of Terra as
an excellent university colleague.
It is much cheaper than Sol while remaining close to GPT-5.5-level capability. OpenAI describes it as the balanced model for everyday work.
Typical tasks
- reading PDFs
- summarizing books
- writing emails
- preparing lectures
- translating
- brainstorming
- planning travel
- ordinary programming
If I were preparing one of your weekly seminar handouts,
I’d probably begin with Terra.
Only when we reach the philosophical heart of the lecture would I switch to Sol.
3. GPT-5.6 Luna
Luna is
the pocket notebook.
It is optimized for
- speed
- low latency
- cost
Use Luna when you want
- quick translations
- definitions
- grammar
- rewriting
- short summaries
- everyday questions
It is surprisingly capable, but not intended for sustained deep reasoning.
How I would divide your own work
Knowing the kinds of conversations we’ve had over the past months, I would divide your workflow like this.
Luna
- translate German
- explain terminology
- check English
- summarize one paper
Terra
- read 30-page articles
- compare three books
- prepare teaching slides
- literature searches
- revise manuscripts
Sol
- “What is a world?”
- “How should psychoanalysis change after AI?”
- “How do Heidegger and Deleuze unexpectedly converge?”
- constructing your own philosophy
- designing new clinical concepts
That is exactly where Sol shines.
What is Codex?
Codex is not another language model.
It is
an AI software engineer built around GPT models.
Instead of merely answering questions, Codex can
- inspect an entire codebase
- edit multiple files
- run tests
- fix bugs
- execute commands
- iterate until software works
GPT thinks.
Codex does work.
Recent releases integrate GPT-5.6 (Sol, Terra, and Luna) into Codex, letting users choose the model and reasoning effort for coding and agent workflows.
Why Codex matters even if you don’t program
This is actually where I think you’ll become interested.
You have repeatedly asked me
“How can AI become a collaborator rather than merely answer questions?”
Codex is one answer.
Imagine saying
Build me a searchable psychoanalytic library.
Codex can
- write the software
- create databases
- build a website
- debug it
- revise it
- continue tomorrow
without you touching the code.
An example from your own work
Suppose you want
「精神分析十四萬篇（PEP-Web）閱藏系統」
Today you might ask me
summarize this paper.
With Codex, you could instead ask
Build software that
- indexes every paper
- extracts authors
- links concepts
- compares Klein, Kohut, Winnicott and Ogden
- lets me search by concepts instead of keywords
- produces lecture notes automatically
That becomes an engineering project.
Codex is designed for exactly this kind of work.
The biggest conceptual shift
I actually think the biggest change in GPT-5.6 is not Sol.
It is that OpenAI is beginning to separate
- thinking
- working
ChatGPT increasingly becomes
a thinking partner.
Codex becomes
a working partner.
And newer agentic products aim to combine both: reasoning about a task and then carrying it out using tools and external services.
My recommendation for you
If I were designing your workflow, it would look like this:
- Luna — capture ideas, translate, ask quick questions while reading.
- Terra — read books, organize notes, prepare seminars, summarize literature.
- Sol — develop your original philosophy, refine your lectures, and explore questions where no established answer exists.
- Codex — build the digital infrastructure around your work: searchable archives, websites, AI-assisted research tools, and software for managing your psychoanalytic corpus.
From our conversations over the past year, I suspect Sol and Codex will have the greatest long-term impact on your work—not because they produce better prose, but because they support the two activities you value most: pursuing genuinely original ideas and constructing an enduring intellectual “world” around them.
