GPT-5.6 Family (Sol, Terra, Luna): API Access and Model Choice Guide

GPT-5.6 landed on the API a few days ago, and OpenAI used the release to rethink naming: instead of another round of suffixes, the generation ships as a three-tier family — Sol, Terra, and Luna. The sun–earth–moon metaphor is the actual product structure: gpt-5.6-sol is the flagship, gpt-5.6-terra the price-performance workhorse, and gpt-5.6-luna the fast, economical tier for volume work. All three carry a 1M+ token context window, and each has a -pro variant.

This guide walks through the tiering logic, which model fits which job, when the -pro variants earn their premium, how to send your first request in Python and curl, and what migrating from GPT-5.5 actually involves (spoiler: one line). Every example runs on Onysoft AI Gateway, which serves the GPT-5.6 family alongside 708+ models behind a single OpenAI-compatible endpoint — whether you are calling from the US, Europe, or Turkey.

Sol, Terra, Luna: How the 5.6 Generation Is Tiered

OpenAI named this generation's tiers after celestial bodies, and the lineup reads at a glance:

• openai/gpt-5.6-sol — the Sun: the flagship and most capable member, built for the hardest reasoning, planning, and coding work.
• openai/gpt-5.6-terra — the Earth: the balanced tier, the default for most production workloads.
• openai/gpt-5.6-luna — the Moon: the economical, fast tier for high-volume and latency-sensitive jobs.

All three ship with a 1M+ token context window, and that is one of the generation's most consequential design choices: stepping down a tier no longer means giving up context. Luna sees just as wide a window as Sol; the tiers differ in capability against task difficulty, not in how much you can show them.

They all speak the same Chat Completions surface, so moving between tiers is nothing more than editing the model field. The previous gpt-5.5 and gpt-5.4 series remain available, so nothing forces a rushed migration. You can compare the full lineup side by side on the GPT models page.

Which Tier for Which Job? Concrete Scenarios

Map tiers to job types, not to an abstract power ranking:

• Reach for Sol when the task is the hard ten percent: autonomous agent runs that last hours, multi-step refactors across a large monorepo, dense legal or technical document analysis, architecture decisions that have to be right the first time.
• Start with Terra for production chatbots, RAG pipelines, coding assistance, and the routine steps of agent workflows. For most teams this is the default — which is exactly why the code examples below use it.
• Drop to Luna for classification, summarization, extraction, moderation, pipelines pushing hundreds of thousands of calls a day, and user-facing features where latency is the product.

A practical loop: prototype on Terra, escalate to Sol at the exact point where Terra loses the thread, and demote every call that feels like overkill to Luna. Because all three share the 1M+ window, demotion rarely requires re-architecting your context handling — which was the usual blocker in earlier generations. Current pricing lives in the model catalog, and our cost-optimization guide shows what disciplined tier routing saves on real traffic.

When Do the -pro Variants Earn Their Premium?

Each tier has a -pro sibling: openai/gpt-5.6-sol-pro, openai/gpt-5.6-terra-pro, and openai/gpt-5.6-luna-pro. The positioning follows OpenAI's established pro pattern: same tier, but aimed at workloads where output quality is prioritized ahead of latency and cost.

Two questions keep the decision clean:

1. Is the tier wrong, or just not deep enough? If Terra produces the right kind of answer but not reliably enough, try terra-pro. If the task belongs to a different league altogether — long-horizon autonomous planning, say — skip the pro detour and move up to sol instead.
2. Per-request or default? Never make -pro your default. Route to it per request: overnight batch jobs, content that ships without human review, critical code generation — anything in the "can wait, cannot be wrong" bucket.

The good news: since all six models sit behind the same endpoint, this routing is a single field in the request body. In most agent frameworks, a "critical step = -pro" rule is one line of configuration, and you can roll it back just as fast if the quality delta does not justify the spend on your workload.

Quick Start: Your First Request in Python and curl

Onysoft is OpenAI-compatible, so you connect to GPT-5.6 with the OpenAI SDK you already use — only the base_url and the key change. Keys use the sk-ony- prefix. Here is the balanced tier, Terra, in action:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.onysoft.com/v1",
    api_key="sk-ony-YOUR-KEY",
)

resp = client.chat.completions.create(
    model="openai/gpt-5.6-terra",
    messages=[{"role": "user", "content": "Summarize this log file and flag the root cause."}],
    stream=True,
)

for chunk in resp:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="")

The same request with curl:

curl https://api.onysoft.com/v1/chat/completions \
  -H "Authorization: Bearer sk-ony-YOUR-KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-5.6-terra",
    "messages": [{"role": "user", "content": "Hello GPT-5.6"}]
  }'

Escalating to Sol or dropping to Luna means changing only the model field. Keep streaming on for long responses. And a note of restraint: the 1M+ window is tempting, but input tokens are billed too — fill it because the task needs it, not because it fits. All parameters are covered in the API documentation, and the Playground lets you compare the three tiers side by side without writing code.

Migrating from GPT-5.5: One Line, No Drama

GPT-5.6 introduces no API break: same Chat Completions endpoint, same parameters, same streaming behavior. Migration is a model-string edit:

• 5.5 on flagship duty → openai/gpt-5.6-sol
• General production load on 5.5 → openai/gpt-5.6-terra
• Economy-class, high-volume calls → openai/gpt-5.6-luna

Two notes from the trenches. First, the gpt-5.5 and gpt-5.4 series are still served, so nothing forces a rushed cutover. Shift a small percentage of traffic to 5.6, measure quality and latency on your own workloads, then expand. Prompts generally carry over as-is, but run your critical prompts through a regression set before flipping the default. Second, the naming scheme moved from version numbers to celestial tiers — if you keep the model name in a single environment variable rather than scattered through the codebase, the next generation's migration stays a one-liner too.

Access Steps, From Anywhere

You do not need a separate OpenAI account to use GPT-5.6 — one Onysoft account covers the whole family:

1. Sign up — an email address gets you an account in minutes.
2. Top up your balance — pay-as-you-go, no subscription. Users in Turkey pay in TL at the central-bank rate with corporate e-invoicing; no foreign card or VPN required.
3. Create your sk-ony- prefixed API key from the dashboard.
4. Pick openai/gpt-5.6-terra in the Playground and test without writing code — then run the same prompt against Sol and Luna to feel the tier differences.
5. Point your app's base_url to https://api.onysoft.com/v1 and ship.

The same key reaches far beyond the 5.6 trio: Claude, Gemini, Grok, and DeepSeek included, 708+ models sit behind one OpenAI-compatible endpoint, operated with KVKK (Turkish data-protection) compliance and 24/7 support. A side benefit of standing behind one gateway is resilience — when a provider has an outage, swapping the model name gets you back up in minutes.