GPT Image 2.5 is live — OpenAI's newest image model, targeted edits that leave the rest of the frame alone
All Posts
GPT-6 Luna vs 5.6 Luna vs 5.6 Terra: Price and Which to Use
2026/10/07

GPT-6 Luna vs 5.6 Luna vs 5.6 Terra: Price and Which to Use

GPT-6 Luna vs 5.6 Luna and 5.6 Terra: OpenAI list prices, the official reason Luna got cheaper, what the benchmarks and early A/B tests show, and which to pick.

GPT-6 Luna vs 5.6 Luna looks like an easy upgrade on paper. OpenAI lists GPT-6 Luna at $0.10 per million input tokens and $0.50 per million output tokens, against $0.20 and $1.20 for GPT-5.6 Luna[1]. It also has a newer knowledge cutoff and the same 1,050,000-token context window[2][3].

The harder questions are the ones developers keep asking: why the newer model costs less, whether it is weaker, and where GPT-5.6 Terra fits now that there is no GPT-6 Terra. This article puts the official prices and specs side by side, quotes OpenAI's stated reason for the price, separates vendor benchmarks from early user tests, and ends with a pick-by-workload recommendation.

TL;DR

  • Price: GPT-6 Luna lists at $0.10 input / $0.01 cached input / $0.50 output per 1M tokens. GPT-5.6 Luna is $0.20 / $0.02 / $1.20, and GPT-5.6 Terra is $2 / $0.20 / $12[1].
  • Why it is cheaper: OpenAI says improvements in caching and inference let it serve the GPT-6 models at lower cost, and it passed the savings on as a cut from the GPT-5.6 prices[4]. It gives no other reason.
  • Specs: context window, max input, max output and the six reasoning-effort levels are identical. GPT-6 Luna's knowledge cutoff is May 18, 2026, against February 16, 2026 for GPT-5.6 Luna[2][3].
  • OpenAI's benchmarks: at high effort, GPT-6 Luna scores 5.4 points higher than its predecessor on AutomationBench at 58% lower cost per task[4].
  • Early users disagree in places: one 10-task A/B test found GPT-6 Luna faster but GPT-5.6 Luna better on first-pass and review quality[5].
  • There is no GPT-6 Terra. OpenAI's GPT-6 lineup is Astra, 6.1 Sol and Luna; Terra exists only as GPT-5.6 Terra[6][7].

GPT-6 Luna vs 5.6 Luna vs 5.6 Terra on the spec sheet

All three are reasoning models that take text and image input and return text. OpenAI positions GPT-5.6 Luna as roughly the nano tier of earlier GPT-5 families and GPT-5.6 Terra as roughly the mini tier[3][8]. GPT-6 Luna is described as "our most efficient model for focused, high-volume tasks"[2].

GPT-6 LunaGPT-5.6 LunaGPT-5.6 Terra
Model IDgpt-6-lunagpt-5.6-lunagpt-5.6-terra
ReleasedSeptember 22, 2026July 9, 2026July 9, 2026[9]
Context window1,050,0001,050,0001,050,000
Max input tokens922,000922,000922,000
Max output tokens128,000128,000128,000
Knowledge cutoffMay 18, 2026Feb 16, 2026Feb 16, 2026
Reasoning effortnone, low, medium (default), high, xhigh, maxsame sixsame six
Input / outputText, image / textText, image / textText, image / text

Sources: the three OpenAI model pages[2][3][8].

Two smaller differences matter in practice. GPT-6 Luna's model page says Chat Completions supports function calling only with reasoning_effort set to none on OpenAI's own API, and recommends the Responses API for tools[2]. And on September 25, OpenAI fixed an image-encoding bug that had degraded image understanding in GPT-6 Sol and Luna, recommending that users rerun image evaluations done before that date[9].

Prices side by side

All figures are OpenAI's Standard list prices per 1M tokens, retrieved October 7, 2026. "Long context" means prompts above 272K input tokens, which re-price the whole request[1].

Per 1M tokensGPT-6 LunaGPT-5.6 LunaGPT-5.6 Terra
Input$0.10$0.20$2.00
Cached input$0.01$0.02$0.20
Cache writes$0.125$0.25$2.50
Output$0.50$1.20$12.00
Long-context input$0.20$0.40$4.00
Long-context output$0.75$1.80$18.00
Batch input / output$0.05 / $0.25$0.10 / $0.60$1.00 / $6.00

The input cut is exactly 50%. Output falls from $1.20 to $0.50, which works out to 58% lower, even though OpenAI's announcement table labels both rows "50% cheaper"[4]. Against GPT-5.6 Terra, GPT-6 Luna is 20 times cheaper on input and 24 times cheaper on output.

As an illustration, take a month with 100M input tokens and 20M output tokens, all uncached and under 272K per prompt:

ModelInput costOutput costMonth
GPT-6 Luna100 × $0.10 = $1020 × $0.50 = $10$20
GPT-5.6 Luna100 × $0.20 = $2020 × $1.20 = $24$44
GPT-5.6 Terra100 × $2 = $20020 × $12 = $240$440

This holds the token counts fixed, which real workloads do not. Reasoning tokens bill as output[10], and OpenAI says GPT-6 Sol and Luna give "slightly shorter answers overall"[4]. Measure output tokens per task on your own prompts before trusting any monthly projection. For a full calculator with caching and long-context cases, see GPT-6 Luna API pricing.

Why GPT-6 Luna is cheaper than GPT-5.6 Luna

OpenAI's launch post gives one reason, in its own words: "Improvements in caching and inference let us serve these models at lower cost, and we're passing those savings directly on to users and customers by reducing API prices for Sol and Luna by 50% compared with their GPT‑5.6 promotional pricing."[4] The same post says GPT-6 Sol and Luna were trained "with similar methods as GPT‑6 Astra" and describes them as advancing "the frontier on cost efficiency"[4].

That is the whole official explanation. OpenAI does not say the model is smaller, and it does not attach an end date to GPT-6 Luna's price. The only promotional window in its pricing notes is for GPT-5.6 Sol, "available at least through November 21, 2026"[1].

The price history adds context. GPT-5.6 Luna itself got cheaper after launch: OpenAI's changelog records that "Starting July 30, GPT-5.6 Luna costs 80% less," with no reason given[9]. The $0.20 / $1.20 baseline that GPT-6 Luna halves is that already-reduced price.

The caching changes also lower effective cost beyond the list rate. OpenAI says it improved prompt caching for GPT-6 "to deliver higher cache hit rates by default," with cached reads billed at a 90% discount[4].

What OpenAI measured against the predecessor

These figures come from OpenAI's announcement and were run by OpenAI. No independent replication had been published when we checked.

  • AutomationBench (business workflows across 47 tools): at high effort, GPT-6 Luna improves on its predecessor by 5.4 percentage points at 58% lower cost per task[4].
  • Factuality (OpenAI's internal evaluation on de-identified conversations where users had flagged errors): "at higher effort levels it matches GPT‑5.6 Sol at about a hundredth its cost"[4].
  • OSWorld 2.0 offline (computer use): GPT-6 Luna at max effort exceeds GPT-5.6 Sol at medium effort "at one tenth of its cost"[4].
  • DeepSWE 1.1 (long-horizon software engineering): GPT-6 Luna at max effort scores 66.6%, which OpenAI calls comparable to Claude Opus 5 and Fable 5 at medium effort[4].

Two limits apply. OpenAI did not publish a GPT-6 Luna vs GPT-5.6 Terra comparison, so any Terra ranking is inference. And several of the strongest Luna results are at max effort, which produces more reasoning tokens and therefore more billed output.

What early users report

Developer reports point both ways, and none of them is a controlled study.

One r/codex user ran GPT-5.6 Luna High and GPT-6 Luna High through 10 tasks on the same ~60k-line C++/Python codebase, with GPT-5.6 Sol judging. GPT-6 Luna won implementation speed 6–4 and used fewer tool calls. GPT-5.6 Luna won first-pass quality 5–3 and review quality 4–2, and the judge preferred its final code 6–4. The author's read: GPT-6 Luna "looks strong for narrow implementation work while Luna 5.6 looks stronger when the task has a wider integration surface"[5].

An r/OpenAI user maintaining an agentic reporting tool reported the opposite of OpenAI's headline at high effort. In their A/B tests GPT-6 Luna missed relevant items that GPT-5.6 Luna found, and appeared "to try to answer the prompt in the least amount of tokens possible"[11].

Both are single users with small samples. Still, they fit OpenAI's own note about shorter answers. If your product depends on exhaustive lists or long explanations, test that specifically.

Where GPT-5.6 Terra fits

Searches for "gpt 6 luna vs terra" assume a GPT-6 Terra. OpenAI does not list one: its GPT-6 guide names GPT-6 Astra, GPT-6.1 Sol and GPT-6 Luna[7], and its model catalog has no gpt-6-terra page[6]. Terra exists only as GPT-5.6 Terra, the mid tier of the previous generation.

So the real comparison is GPT-6 Luna against GPT-5.6 Terra at 20–24 times the price. OpenAI has not benchmarked that pair. What it has published is that GPT-6 Luna at high or max effort matches or beats GPT-5.6 Sol on two of its evaluations[4]. GPT-5.6 Sol is the tier above Terra. That is suggestive, not proof. Keep Terra in production only where your own evaluation shows it winning on the tasks you run. For the GPT-6 tiers above Luna, see GPT-6 Sol vs Luna.

Moving from gpt-5.6-luna to gpt-6-luna

On reAPI both models run on the same Chat Completions endpoint with the same API key, so the switch is the model string. Check four things before moving traffic:

  1. Reasoning effort. Both accept the same six levels with medium as the default[2][3]. Start at the level you use today and compare output tokens per task as well as accuracy.
  2. Sampling parameters. OpenAI's GPT-6 migration guide says to remove temperature, top_p and top_logprobs when reasoning effort is not none[7]. On reAPI, GPT-6 Luna returns 400 for temperature and top_p[12]. See GPT-6 Luna temperature for details.
  3. Answer length. If downstream code or users expect long answers, check completeness, not just correctness.
  4. Images. Re-run image evaluations if any were done before the September 25 fix[9].

Current reAPI rates for each model are on its page: GPT-6 Luna, GPT-5.6 Luna and GPT-5.6 Terra.

FAQ

Why is Luna 6 cheaper than Luna 5.6?

OpenAI says improvements in caching and inference let it serve GPT-6 Sol and Luna at lower cost, and it passed those savings on by cutting prices 50% from GPT-5.6's pricing[4]. It gives no other reason and no end date for the GPT-6 Luna price.

Is GPT-6 Luna weaker?

Not on OpenAI's published numbers: at high effort it beats GPT-5.6 Luna by 5.4 points on AutomationBench at 58% lower cost per task[4]. Some users report weaker results on review-heavy or exhaustive tasks, including one 10-task A/B test that favoured GPT-5.6 Luna's quality[5]. Test on your own prompts.

Is gpt 6 luna higher than terra?

There is no GPT-6 Terra to compare with[6][7]. Against GPT-5.6 Terra, OpenAI has published no head-to-head benchmark. GPT-6 Luna costs a twentieth of Terra's input rate and a twenty-fourth of its output rate[1].

gpt 6 luna vs 5.6 sol

GPT-5.6 Sol lists at $4 input and $20 output per 1M tokens, 40 times GPT-6 Luna's rates[1]. OpenAI reports GPT-6 Luna at higher effort matching GPT-5.6 Sol on its factuality evaluation, and Luna at max effort beating Sol at medium on OSWorld 2.0 offline[4].

Why is GPT-5.6 Luna so cheap?

OpenAI cut GPT-5.6 Luna's price by 80% on July 30, 2026, and its changelog gives no reason for the cut[9]. It is still more expensive than GPT-6 Luna.

How much does gpt-5.6 Luna cost?

OpenAI lists GPT-5.6 Luna at $0.20 input, $0.02 cached input, $0.25 cache writes and $1.20 output per 1M tokens. Prompts above 272K input tokens cost $0.40 input and $1.80 output, and Batch is half the Standard rate[1].

Am I actually losing much by going back to 5.6 Luna high instead of using 6 Luna xhigh/max?

On price, GPT-5.6 Luna charges 2.4 times GPT-6 Luna's output rate, while xhigh and max produce more reasoning tokens that bill as output[1][10]. OpenAI's AutomationBench gain for GPT-6 Luna over its predecessor is reported at high effort[4], so GPT-6 Luna at high is a reasonable first test before paying for xhigh or max. Compare cost and accuracy per finished task on your own workload.

Choosing between GPT-6 Luna and 5.6 Luna

For new high-volume work, start with GPT-6 Luna. It halves the input price, cuts output by 58%, has a newer knowledge cutoff, and wins OpenAI's own comparisons with GPT-5.6 Luna. Keep GPT-5.6 Luna where a validated production prompt depends on long or exhaustive answers until a side-by-side test says otherwise, since that is where users have reported regressions. Use GPT-5.6 Terra only where your evaluation shows the extra 20–24× price buying accuracy you need.

That settles GPT-6 Luna vs 5.6 Luna for most teams: test GPT-6 Luna first, and keep the older model where your evaluations show it doing better.

References

  1. OpenAI. API pricing. Retrieved October 2026 from developers.openai.com/api/docs/pricing
  2. OpenAI. GPT-6 Luna model page. Retrieved October 2026 from developers.openai.com/api/docs/models/gpt-6-luna
  3. OpenAI. GPT-5.6 Luna model page. Retrieved October 2026 from developers.openai.com/api/docs/models/gpt-5.6-luna
  4. OpenAI. Introducing GPT-6 Sol and Luna. Retrieved October 2026 from openai.com/index/introducing-gpt-6-sol-and-luna
  5. Reddit r/codex. I A/B tested GPT-5.6 Luna and GPT-6 Luna on the same engineering tasks. Retrieved October 2026 from reddit.com/r/codex/comments/1wp7ckc
  6. OpenAI. Models. Retrieved October 2026 from developers.openai.com/api/docs/models
  7. OpenAI. Using GPT-6. Retrieved October 2026 from developers.openai.com/api/docs/guides/latest-model
  8. OpenAI. GPT-5.6 Terra model page. Retrieved October 2026 from developers.openai.com/api/docs/models/gpt-5.6-terra
  9. OpenAI. API changelog. Retrieved October 2026 from developers.openai.com/api/docs/changelog
  10. OpenAI. Reasoning models. Retrieved October 2026 from developers.openai.com/api/docs/guides/reasoning
  11. Reddit r/OpenAI. Luna 6 is a massive downgrade over Luna 5.6. Retrieved October 2026 from reddit.com/r/OpenAI/comments/1wnxg0n
  12. reAPI. GPT-6 Luna API docs. Retrieved October 2026 from reapi.ai/docs/gpt-6-luna
All Posts

More Posts