Quick answer
- Rational default
- GPT-5.6 Terra, $2.5 in / $15 out per MTok
- Flagship
- GPT-5.6 Sol, $5 in / $30 out per MTok, only tier with max effort + ultra mode
- Budget tier
- GPT-5.6 Luna, $1 in / $6 out per MTok
- Current generation since
- July 9, 2026 (GPT-5.6 GA)
The Current Codex Roster
As of July 18, 2026, the current generation in Codex is the GPT-5.6 family, three tiers that went GA on July 9, 2026: GPT-5.6 Sol, GPT-5.6 Terra, and GPT-5.6 Luna. Also selectable, per OpenAI's Codex docs: GPT-5.5 (the previous flagship), GPT-5.4, GPT-5.4 Mini, and GPT-5.3 Codex Spark, a text-only research preview limited to ChatGPT Pro. Deprecated for ChatGPT sign-in: gpt-5.2 and gpt-5.3-codex.
You do not have to pick at all: by default Codex auto-selects, and the default tracks the recommended model. This guide is for when you want to make the trade-off deliberately, because per the pricing below, the difference between tiers is 2x or more per token.
What the Names Mean, and What Each Tier Costs
OpenAI's scheme is simple once decoded: the number is the generation (5.5, 5.6), the name is the capability tier within it. Sol is the flagship, Terra the workhorse, Luna the budget tier. Verified prices and positioning for every OpenAI model currently in Codex:
| Model | Tier | Price | Positioning |
|---|---|---|---|
| GPT-5.6 Sol | frontier | $5 in / $30 out per MTok | OpenAI's brand-new flagship, the only GPT-5.6 tier with max reasoning effort and ultra mode (parallel subagents). |
| GPT-5.6 Terra | workhorse | $2.5 in / $15 out per MTok | The everyday workhorse: roughly GPT-5.5 performance at about half the price. |
| GPT-5.6 Luna | fast | $1 in / $6 out per MTok | The budget/fast tier of the GPT-5.6 family. |
| GPT-5.5 | flagship | $5 in / $30 out per MTok | The previous OpenAI flagship, still available in Codex; Terra now matches it for half the price. |
The row that matters most: GPT-5.6 Terra delivers roughly GPT-5.5 performance at about half GPT-5.5's price ($2.5/$15 vs $5/$30 per MTok). That single fact makes Terra the rational default for most sessions, the flagship is for escalation, not for everything.
Benchmarks: A Small Gap, a 2x Price Gap
OpenAI's launch materials report Terminal-Bench 2.1 for all three 5.6 tiers, which makes the within-family comparison unusually clean:
| Model | Terminal-Bench 2.1 | Price (per MTok) |
|---|---|---|
| GPT-5.6 Sol | 88.8% (91.9% in ultra mode) | $5 / $30 |
| GPT-5.6 Terra | 87.4% | $2.5 / $15 |
| GPT-5.6 Luna | 84.7% | $1 / $6 |
Read the spread carefully: Sol beats Terra by 1.4 points while costing twice as much per token. Ultra mode widens Sol's lead to 91.9%, but that is a Sol-only capability, not a reason to run Sol on routine edits. Luna gives up 4.1 points against Sol for a fraction of the price, which is exactly the profile you want for mechanical work. How Sol stacks up outside the family, against Anthropic's frontier model, is a messier question we cover in Claude Fable 5 vs GPT-5.6 Sol.
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Reasoning Effort, Explained
Model choice is only half the Codex tuning surface. The other half is reasoning effort: how much the model thinks before and between actions. Codex exposes the levels minimal, low, medium, high, and xhigh, plus a max level that only GPT-5.6 Sol supports. You can change it per-session, or set a persistent default in Codex's config file:
# ~/.codex/config.toml
model = "gpt-5.6-terra"
model_reasoning_effort = "high"Practical guidance: turn effort up for planning, architecture decisions, and debugging gnarly issues, the runs where a wrong early step costs you the whole session. Turn it down for mechanical edits, renames, and test fixes, where extra thinking is just extra latency and spend. On top of the effort ladder, Sol adds ultra mode, which runs parallel subagents natively, the same idea behind parallel agents on git worktrees, but inside a single model run.
The Decision Guide
- 1
Default to GPT-5.6 Terra
GPT-5.5-class capability at about half the price, and within 1.4 points of Sol on Terminal-Bench 2.1. Set it once at $2.5 in / $15 out per MTok and stop thinking about it for routine implementation. - 2
Escalate to GPT-5.6 Sol for hard or long agentic runs
When the story is genuinely hard, a long autonomous run, a tangled debugging session, or work that benefits from ultra mode's parallel subagents or max reasoning effort, pay the 2x. One avoided failed run covers the difference. - 3
Drop to GPT-5.6 Luna for cheap mechanical work
Renames, lint fixes, high-volume small tasks. At $1 in / $6 out per MTok it is the cheapest 5.6 tier, and its 84.7% Terminal-Bench score is plenty for work you review anyway. - 4
GPT-5.5 only if your workflow is tuned to it
It is proven and still available, but Terra matches it at half the price. Migrate when convenient; do not start new setups on it. - 5
Treat Codex Spark as an experiment
GPT-5.3 Codex Spark is a text-only research preview, ChatGPT Pro only. Interesting to poke at, not a tier to build on.
Per-Story Model Choice, One Board
The tier system only pays off if switching is cheap. That is where AIDEN fits: a macOS desktop app that orchestrates your existing Codex CLI alongside Claude Code on one kanban board, BYOK and local-first, with every story gated behind an approved spec. Each story card gets its own git branch and its own agent, so Sol takes the hard migration, Terra the routine features, and a Claude model whichever story suits it, in the same project. The full comparison with running Codex bare is in AIDEN vs Codex CLI, and every current model across both vendors is on the models hub.