Skip to main content
AI Choice Engine
Back to blog

How-to

Migrating from GPT-5.6 to GPT-6 Sol and Luna — Prices, Model IDs, Caching, and What Breaks

OpenAI's GPT-6 Sol and Luna halve the GPT-5.6 API prices, and GPT-5.6 Sol's promo price ends in November. Here is what changes when you switch model IDs, what to re-test, and how to cut over safely.

Published September 26, 20266 min readAI ToolsBy AI Choice Engine Editorial

Prices and dates checked on 26 September 2026 against OpenAI's announcement and the other sources at the end.

On 22 September 2026 OpenAI released GPT-6 Sol and GPT-6 Luna, trained with similar methods to GPT-6 Astra. For API customers, the news is in one table: both cost half their GPT-5.6 predecessors. GPT-5.6 Sol's current price is itself a promotion that ends on 21 November 2026. So most teams on GPT-5.6 Sol or Luna should plan a migration now rather than after the cliff.

This is the checklist. It covers what changes, what to re-test, and how to cut over without breaking production.

What changes: IDs and prices

Old IDNew IDOld price (in / out per 1M)New priceChange
gpt-5.6-solgpt-6-sol$4 / $20 (promo until 21 Nov; list $5 / $30)$2 / $10−50% vs promo, −60% input and −67% output vs list
gpt-5.6-lunagpt-6-luna$0.20 / $1.20$0.10 / $0.50−50% input, −58% output
gpt-5.6-terra— (no GPT-6 Terra announced)$2 / $12—Stay, or test GPT-6 Sol, which now lists at the same input price and a lower output price

What the savings look like at a steady monthly volume of 100M input and 20M output tokens:

WorkloadGPT-5.6GPT-6After 21 Nov if you stay on GPT-5.6 Sol
Sol$800$400$1,100 (at the $5/$30 list)
Luna$44$20—

Those figures ignore caching, which makes the new models cheaper still.

What changes: caching

OpenAI shipped caching changes with GPT-6 that matter for agents and long conversations:

  • Higher cache hit rates by default, with a 90% discount on cached input-token reads.
  • Changing reasoning effort or tool availability no longer breaks the cache. You can raise effort for a hard step, or switch tools on and off mid-conversation, and earlier context stays reusable.
  • Explicit breakpoints let you choose where a cached prefix ends.
  • A Prompt Caching Dashboard and a diagnostics tool show what is cached and explain missed opportunities.

Migration action: if your application reorders the system prompt, injects timestamps at the top, or rebuilds tool lists per request, fix that first. Stable prefixes are where the 90% discount comes from. Check the dashboard in week one; a low hit rate usually means a prompt-assembly bug, not a model problem.

What can break

Price is the easy part. These are the things to re-test:

  1. Output shape. OpenAI says GPT-6 Sol and Luna answer with "more clarity, less jargon, fewer odd turns of phrase… and slightly shorter answers overall." That is good for users and risky for code that parses responses. Check length-based heuristics, regex extractors, and any eval that rewards verbosity.
  2. Your quality bar. OpenAI reports that GPT-6 Sol makes about half as many factual mistakes as GPT-5.6 Sol on its internal evaluation. It also says GPT-6 Luna at higher effort matches GPT-5.6 Sol at about a hundredth of the cost. These are vendor claims. Your acceptance tests decide whether Luna can take over work that Sol used to do.
  3. Effort settings. If you tuned a reasoning-effort level on GPT-5.6, re-tune it. The same label on a new model does not guarantee the same latency or token use.
  4. Long-context pricing and limits. The limits carry over: GPT-6 Sol and Luna keep the 1.05M-token context and 128K max output of their GPT-5.6 predecessors. The long-context step also stays at 272K input tokens. Above it, the whole request bills $4/$15 on Sol ($0.40 cached) and $0.20/$0.75 on Luna. Cache writes cost 1.25× input: $2.50 per million on Sol and $0.125 on Luna. Re-run your cost model for any workload that regularly crosses 272K.
  5. Pinned aliases and dashboards. Search config, infrastructure-as-code, and billing dashboards for gpt-5.6-. Mixed IDs make a cost spike hard to read.
  6. ChatGPT is not the API. In ChatGPT, GPT-6 Sol and Luna are in Work and Codex for Plus, Pro, Business, Enterprise and Edu. They are not yet in Chat. On Enterprise plans an admin must enable them. Do not use the Chat window to judge the API model.

A two-week migration plan

Days 1–2: inventory. List every call site, its current model ID, monthly tokens, and owner. Mark which ones have automated validators and which rely on humans spotting problems.

Days 3–5: shadow traffic. Send a copy of real requests to the GPT-6 ID behind the same adapter, without serving the result. Compare validator pass rates, output length, latency, and cost per request. Freeze 20–30 hard prompts per workload as a regression set.

Days 6–8: caching check. Turn on caching diagnostics for the GPT-6 route. Fix prompt-assembly issues until the hit rate matches what the workload's structure should allow.

Days 9–12: staged cutover. Move 10%, then 50%, then 100% of traffic per workload, holding each step for at least a day. Keep the GPT-5.6 route warm as a one-line rollback.

Days 13–14: tier review. Now that Sol costs no more per token than GPT-5.6 Terra, check whether Terra workloads should move to Sol. Check whether some Sol workloads pass on GPT-6 Luna. The OpenAI tier guide covers the routing logic.

Finish before 21 November, when GPT-5.6 Sol's promotional price is scheduled to end.

When not to migrate yet

  • Regulated outputs with sign-off. If a workflow's outputs were validated by compliance or legal on GPT-5.6, budget for that review again. The price saving does not skip it.
  • Workloads that run in ChatGPT, not the API. Migrating there depends on OpenAI's rollout, not your code.
  • A frontier-model decision is pending. If you are also weighing Anthropic, test both at once. GPT-6 Sol vs Claude Opus 5.5 has the cost-per-task framing.

For a shortlist scored against your constraints, use the AI Model Picker. If the model sits inside a coding tool rather than your own code, the AI Coding Assistant Finder covers the harness side.

Sources (accessed 2026-09-26 unless noted)

Editorial note

AI Choice Engine publishes editorial guides to help readers understand fit, trade-offs, and next steps before choosing a tool or provider.

Newsletter

Get the buyer checklist that goes with this guide

Subscribe to download the matching checklist. Automated email delivery is still rolling out — this is not an inbox confirmation.

A practical scorecard for comparing fit, cost, rollout risk, support, and lock-in.

Updates only — checklists stay free from the resource library, with or without joining. Automated email delivery is still rolling out.

Next step

Use the live tool while the trade-offs are still fresh

The article gives context. The live tool turns those trade-offs into a clearer shortlist.

Buying guides

Guide pages connected to this article

These guides go one level deeper for readers who want a longer-form buying view before choosing a provider.

Keep reading

More articles in the same decision path

These pieces stay inside the same research journey instead of sending you somewhere unrelated.

  1. ChatGPT Free vs Plus in 2026 — Luna, Think, and the Sol sliderOpenAI’s August 2026 ChatGPT refresh changed the free tier more than the API. Here is how Free/Go vs Plus/Pro actually differ — and what still bills separately.
  2. ChatGPT Work vs Chat vs Codex — which OpenAI surface are you buying?Chat got the August Sol refresh first; Work and Codex got GPT-6 Sol and Luna first in September. The surfaces move on different timelines, so treat them as separate buying decisions.

Next steps

Next step across the network

Continue with a focused hub page instead of restarting your research from scratch.