GPT-5.6 Pricing After the Cut: Luna vs Terra vs Sol, and Which Tier to Use

After O​penAI's July 30, 2026 price cut, the GPT-5.​6 family — GPT-5.6 Luna, GPT-5.6 Terra, and GPT-5.6 Sol — has never been cheaper to run at scale. A week later, on August 6, O​penAI pushed the same tiers into ChatGPT itself: GPT-5.6 Luna is becoming the default model for free and Go accounts with unlimited text chats, while GPT-5.6 Sol was updated for Plus and Pro. But the three tiers are priced very differently, and picking the right one (plus using caching, batch, and routing well) is the single biggest lever on your API bill. This guide lays out the full post-cut pricing, worked cost examples, how each tier compares to rivals, and how to route between them through one endpoint.

Prices are per million tokens (input / output), reflecting the post-cut rate card as reported and OrcaRouter's pass-through model pages; tiered and cache rates come from OrcaRouter's model pages, and competitor figures are attributed. The ChatGPT rollout details in this piece are as O​penAI stated them on August 6, 2026 — vendor-reported, not independently measured. Prices change — verify before building.

TL;DR

GPT-5.6 Luna ($0.20 / $1.20) is the high-volume workhorse; Terra ($2 / $12) is the balanced middle; Sol ($5 / $30) is the flagship for the hardest reasoning and agentic coding. All three share a ~1.05M-token context and 128K max output. Prompt caching and the batch option cut costs further, while very long inputs move you to a higher tier. On the consumer side, O​penAI announced August 6 that GPT-5.6 Luna is becoming the default for Free and Go ChatGPT accounts with unlimited text-only chats, and that an updated GPT-5.6 Sol is rolling out to Plus and Pro. Use Luna for the easy majority, Terra when you need more, and Sol only where it earns its cost — and route by difficulty through one O​penAI-compatible endpoint to minimize spend.

Key takeaways

• Luna: $0.20 / $1.20 per 1M tokens — fast, cheap, for high-volume, latency-sensitive work.

• Terra: $2 / $12 — the balanced mid-tier for tougher tasks that don't need the flagship.

• Sol: $5 / $30 — the flagship for deep reasoning, large-scale coding, long-horizon agents.

• Caching and batch cut costs further; long inputs move you to a pricier long-context tier.

• ChatGPT (O​penAI-stated, Aug 6): Luna becomes the free/Go default with unlimited text chats; Sol gets a reliability update for Plus/Pro.

• Biggest savings lever: route by difficulty — don't pay Sol rates for work Luna can do.

The new GPT-5.​6 base pricing

Here's the post-cut base pricing per million input/output tokens: Luna $0.20 / $1.20 (down from $1 / $6), Terra $2 / $12 (down from $2.50 / $15), and Sol $5 / $30 (unchanged). The two cheaper tiers were cut on July 30, 2026; the flagship held. Put simply, the low tiers are now priced for scale, while the flagship stays premium.

Tiered, cached, and batch pricing

The base rate is only the starting point. GPT-5.​6 pricing has three modifiers that materially change your effective cost:

• Long-context tiers. Prices step up for very long inputs. On OrcaRouter's pass-through pages, Luna is $0.20 / $1.20 up to a large context tier and $0.40 / $1.80 beyond it; Sol is $5 / $30 at its base tier and $10 / $45 at the largest. The tier is chosen by each request's input token count, so a few huge prompts can quietly raise your average price.

• Prompt caching. Reused context is billed at a steep discount — Luna's cache read is roughly $0.02 per million tokens (versus $0.20 fresh), with cache writes around $0.25; Sol's cache read is about $0.50 (versus $5 fresh). For agents and chat with a stable system prompt, caching is often the single biggest saving.

• Batch. Non-urgent jobs run asynchronously at a discount — ideal for bulk classification, evals, and offline generation where latency doesn't matter.

Worked examples: what it actually costs

Concrete numbers make the tiers real. Take 10 million tokens a month with a 70% input / 30% output split (a typical chat/agent mix):

• Luna: about $5 a month (roughly $4.37 with prompt caching).

• Terra: about $50 a month.

• Sol: about $125 a month (roughly $109 with caching).

That's a 25x spread between Luna and Sol for the same volume — which is exactly why matching each request to the cheapest capable tier matters more than any single rate. (These match OrcaRouter's on-page cost calculator, which estimates from list price; your real numbers depend on caching and your input/output mix.)

What each tier is actually for

GPT-5.6 Luna — the volume workhorse

Luna is the fast, cost-efficient tier, tuned for high-volume, latency-sensitive workloads: chat, classification, extraction, routing, and lightweight agentic tasks, with a p50 time-to-first-token around 1.65 seconds. After the cut, at $0.20 / $1.20 it's priced to compete directly with cheap open models — the default for the easy majority of calls. It is also the tier O​penAI is steering consumer ChatGPT toward: per its August 6 announcement, GPT-5.6 Luna is becoming the default model for Free and Go accounts, with text-only chats going unlimited and a new Think button for higher reasoning on harder questions arriving the following week (file, image, and voice limits remain). O​penAI says Luna makes 62% fewer factual errors than the GPT-5.5 Instant it replaces — a vendor-reported figure, but a clear signal that the volume tier is where the company is pointing most of its traffic.

GPT-5.6 Terra — the balanced middle

Terra sits between volume and flagship: more capable than Luna for tougher reasoning and coding, but far cheaper than Sol. At $2 / $12 it's a sensible default when Luna isn't quite enough but you don't need the flagship — mid-complexity extraction, drafting, and multi-step tasks that still run at scale.

GPT-5.6 Sol — the flagship

Sol is built for the hardest work: deep multi-step reasoning, large-scale software engineering, and long-horizon agentic workflows, staying coherent across a ~1.05M-token context and up to 128K output. At $5 / $30 (base) it's a premium choice — reserve it for tasks that genuinely need it, like complex multi-file coding or long agent runs. On August 6, O​penAI also updated GPT-5.6 Sol in ChatGPT for Plus and Pro users: the company says the chat version is more reliable with facts — 68% fewer factual errors, per O​penAI — and gives more focused answers, with a new slider to control how much reasoning effort it applies. The update is chat-only (the Sol behind Work and Codex is unchanged), and the API tier stays at $5 / $30.

The reasoning-token caveat

GPT-5.​6 are reasoning models, so effective output cost can exceed a naive estimate: when reasoning is on, internal reasoning tokens are billed as output. On hard prompts with high reasoning effort, that can dominate your bill. Tune reasoning effort to the task (low or off for simple calls), cap output tokens where you can, and measure actual usage. Cheaper per-token rates help; generating fewer tokens helps more.

How each tier compares to rivals

The cut repositioned GPT-5.​6 against the field. Per reporting, Luna's $0.20 / $1.20 now undercuts Claude Haiku 4.5 by roughly 5x on input and 4x on output, and Terra's $2 / $12 falls below Claude Sonnet 5's standard pricing (reported at $3 / $15). Against open weights, Luna sits near the floor set by Deep​Seek's V4 line and Zhipu's GLM-5.2 (about $1.20 / $4.10), with Qw​en and Gemini Flash tiers nearby. The upshot: for cost-sensitive work, Luna is now competitive with the cheapest capable models rather than a premium alternative to them — while Sol remains a genuine premium tier for capability you can't get cheaply.

The real savings lever: route by difficulty

The cheapest bill isn't a single tier — it's matching each request to the least expensive model that can do it. In practice: send easy, high-volume calls to Luna (or a cheap open model), step up to Terra for harder tasks, and use Sol only for the genuinely difficult minority. Combined with caching and batch, this routinely cuts costs far more than any single price change. The catch is operational: you don't want to re-integrate three O​penAI tiers plus open-model alternatives separately.

Access all three (and cheaper rivals) through one endpoint

This is where a vendor-neutral router helps. OrcaRouter exposes GPT-5.6 Luna, Terra, and Sol — at the same post-cut prices, 0% markup — through one O​penAI-compatible endpoint, alongside cheaper open models like DeepSeek V4 Pro, GLM-5.2, and Qw​en. Switching tiers (or A/B testing Luna against an open model) is a config change, not a re-integration, and you can route each request to whatever is cheapest.

The post-cut Luna rate card is visible on OrcaRouter's own model page at list price — $0.20 / $1.20 per million tokens — because the router passes provider prices through at 0% markup, with an on-page cost calculator for a typical monthly bill. There's also a free tier and an Offers page for additional savings.

FAQ

What are the GPT-5.​6 prices after the cut?

Luna $0.20 / $1.20, Terra $2 / $12, and Sol $5 / $30 per million input/output tokens. Luna and Terra were cut on July 30, 2026; Sol is unchanged.

Which GPT-5.​6 tier should I use?

Luna for high-volume, latency-sensitive work; Terra for tougher tasks that don't need the flagship; Sol for the hardest reasoning and agentic coding. Route by difficulty to minimize cost.

Is GPT-5.6 Luna free in ChatGPT?

O​penAI announced on August 6 that GPT-5.6 Luna is becoming the default model for free and Go ChatGPT accounts, with unlimited text-only chats; limits remain on file uploads, images, and voice tools, and a Think button for higher reasoning is rolling out separately. These are O​penAI-stated plans, not independently verified.

How much does GPT-5.​6 cost per month?

At 10M tokens/month (70% input): roughly $5 on Luna, $50 on Terra, and $125 on Sol — a 25x spread, before caching. Your actual cost depends on caching and your input/output mix.

Do all three tiers have the same context window?

Yes — roughly a 1.05M-token context and up to 128K output tokens, with vision, tools, JSON, and reasoning support.

How does prompt caching affect cost?

Caching sharply reduces repeated-context cost — Luna's cache read is around $0.02 per million tokens versus $0.20 fresh — so reuse cached prompts wherever possible. Long inputs, conversely, can move you to a pricier long-context tier.

How do the tiers compare to Anthropic or open models?

Per reporting, Luna undercuts Claude Haiku 4.5 (~5x input / 4x output) and Terra falls below Claude Sonnet 5 ($3 / $15). Luna is also near the cheap open-model floor (Deep​Seek, GLM-5.2 ~$1.20/$4.10).

Where can I use all three tiers together?

Through OrcaRouter's single O​penAI-compatible endpoint at 0% markup, alongside cheaper open models for difficulty-based routing.

Bottom line

After the cut, GPT-5.6 Luna ($0.20 / $1.20) and Terra ($2 / $12) are compelling for high-volume and mid-tier work, while Sol ($5 / $30) remains the premium flagship — a 25x cost spread that rewards smart routing. The consumer rollout reinforces the split: O​penAI is making Luna the free default while reserving Sol's reliability update for paid plans, which for API builders is one more reason to route easy traffic to Luna. The biggest savings come from routing by difficulty, leaning on caching and batch, and controlling reasoning tokens rather than defaulting to one tier. Doing that is easiest through a single 0%-markup endpoint like OrcaRouter, where all three tiers (at the new prices) sit next to the cheaper open models you'll want to compare them against.