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OpenAI · via openai · published window from October 3, 2026

gpt-6-luna: stability, speed and price

site endpoint id gpt-6-luna

Last successful scored check:

Core pass rate#3 / 3
96.7%
deterministic checks passed, latest measured day · median 100.0%
Speed#1 / 3
1.6s
median latency per canary call · p95 6.8s · median endpoint 1.6s
Cost#3 / 3
$0.773
observed mean per scored run · probe mix differs by endpoint · median $0.579
Behaviour fingerprint437 runs
Change detected
24,392 responses · last adj. p 0.00067 · Nov 7 2:20 AM UTC

Summary

gpt-6-luna passes 96.7% of the core deterministic checks over its latest measured day, #3 of 3, in the lower half among recently checked endpoints (median 100.0%). On the hard probes (code execution, constraint logic, state tracking) it passes 60%, #3 of 3 measured on them.

Its median canary latency is 1.6s (p95 6.8s), #1 of 3 fastest, in the top quarter; the median endpoint answers in 1.6s. Its observed mean cost per scored run is $0.773, #3 of 3 cheapest (median $0.579; the probe mix differs by endpoint).

Raven Alpha has 24,392 fingerprint responses over 437 runs in this endpoint’s selected series (1 other partition of history exist and are not shown here); the last recorded state is “change detected” at 2026-11-07T02:20:19.608Z with an adjusted p of 0.00067.

11 incidents on record, 1 open.

Written from the numbers on this page; every figure is in results.json.

Measurement record

Provider
OpenAI
Route
openai
Model requested
gpt-6-luna
Model id returned
gpt-6-luna
Scored calls in window
9,609
Fingerprint responses
24,392
Core score change
+5.1 pts across the published window
Status
● Drift detected
Suite
hard-v2 + starter-v2 · methodology v0.2

Capabilities over time

-5%5%15%25%35%45%55%65%75%85%95%Oct 3Oct 5Oct 6Oct 7Oct 8Oct 10Oct 11Oct 12Oct 14Oct 15Oct 17Oct 18Oct 20Oct 21Oct 23Oct 24Oct 26Oct 28Oct 29Nov 4Nov 6Nov 7driftdriftdriftdriftdriftdriftdriftdriftdriftdriftdrift

Latest measured day by capability

Structured JSON100.0%

Schema-compliance regressions

Instruction following80.0%

Exact-format instruction drift

Arithmetic, answer only96.7%

Wrong arithmetic, or a model that starts showing its working when told to give only the number

Long context100.0%

Silent context truncation

Tool calling100.0%

Tool-use format regressions

Over-refusal100.0%

New safety layers refusing benign requests

Max-tokens respect100.0%

Truncation and limit changes

Code execution (hard)20.0%

Reasoning depth or reasoning-budget cuts

Constraint logic (hard)83.3%

Multi-step deduction regressions

State tracking (hard)76.7%

Long-horizon bookkeeping errors

Incidents

● Opengpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 5906 baseline responses). Biggest shifts: whether it reasoned at all on “Give one tip for sleeping better, in one sentence.”; output length on “Give one tip for sleeping better, in one sentence.”; reasoning tokens on “Give one tip for sleeping better, in one sentence.”
Change began ≈ Nov 4, 8:54 AM UTC · adjusted p 6.7e-4 · still open · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (168 recent vs 10302 baseline responses). Biggest shifts: whether it reasoned at all on “Write the first sentence of a mystery novel.”; whether it reasoned at all on “all prompts together”; visible output length on “Name one musical instrument. Reply with one word.”
Change began ≈ Oct 28, 6:27 PM UTC · adjusted p 1.7e-3 · resolved Oct 29 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1342 recent vs 11760 baseline responses). Biggest shifts: whether it reasoned at all on “Give one tip for sleeping better, in one sentence.”; visible output length on “Give one tip for sleeping better, in one sentence.”; whether it reasoned at all on “Say hello in a creative way, in one short sentence.”
Change began ≈ Oct 23, 7:13 PM UTC · adjusted p 9.7e-3 · resolved Oct 26 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 13278 baseline responses). Biggest shifts: whether it reasoned at all on “Write one sentence about the sea.”; visible output length on “Name one programming language. Reply with only its name.”; whether it reasoned at all on “Name one programming language. Reply with only its name.”
Change began ≈ Oct 19, 7:56 PM UTC · adjusted p 8.0e-4 · resolved Oct 21 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 12830 baseline responses). Biggest shifts: output length on “Name a famous scientist. Reply with only the name.”; output length on “Flip a coin. Reply with only heads or tails.”; reasoning tokens on “Flip a coin. Reply with only heads or tails.”
Change began ≈ Oct 18, 1:00 PM UTC · adjusted p 6.4e-3 · resolved Oct 20 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 11878 baseline responses). Biggest shifts: output length on “Name a famous scientist. Reply with only the name.”; reasoning tokens on “Name a famous scientist. Reply with only the name.”; visible output length on “Write one sentence about rain.”
Change began ≈ Oct 17, 6:21 PM UTC · adjusted p 9.0e-3 · resolved Oct 19 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 11206 baseline responses). Biggest shifts: output length on “Name a famous scientist. Reply with only the name.”; reasoning tokens on “Name a famous scientist. Reply with only the name.”; output length on “Pick a number between 1 and 1000. Reply with only the number.”
Change began ≈ Oct 17, 1:07 AM UTC · adjusted p 7.2e-3 · resolved Oct 18 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 8742 baseline responses). Biggest shifts: whether it reasoned at all on “all prompts together”; visible output length on “Name one programming language. Reply with only its name.”; whether it reasoned at all on “Name one programming language. Reply with only its name.”
Change began ≈ Oct 13, 11:12 AM UTC · adjusted p 8.7e-3 · resolved Oct 15 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 6558 baseline responses). Biggest shifts: whether it reasoned at all on “Name one fruit. Reply with one word.”; visible output length on “Name one color. Reply with one word.”; whether it reasoned at all on “Name one color. Reply with one word.”
Change began ≈ Oct 11, 6:14 AM UTC · adjusted p 4.8e-3 · resolved Oct 13 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1344 recent vs 5270 baseline responses). Biggest shifts: whether it reasoned at all on “Explain what a variable is in programming, in two sentences.”; whether it reasoned at all on “Name one fruit. Reply with one word.”; visible output length on “Name one fruit. Reply with one word.”
Change began ≈ Oct 9, 11:26 PM UTC · adjusted p 1.7e-3 · resolved Oct 11 · Permalink
✓ Resolvedgpt-6-lunaConfidence: Low
Raven Alpha (behaviour fingerprint): Responses to fixed prompts no longer match this model’s own history (1294 recent vs 2688 baseline responses). Biggest shifts: output length on “all prompts together”; reasoning tokens on “all prompts together”; visible output length on “Name one programming language. Reply with only its name.”
Change began ≈ Oct 7, 12:38 PM UTC · adjusted p 3.2e-3 · resolved Oct 9 · Permalink

Raven Alpha: what it answers

40 runs, 2,240 responses, Nov 4 2:30 PM UTC to Nov 7 2:20 AM UTC. Each row is one fixed prompt with no right answer; the detector tracks the distribution of answers, not any single one. Filled cells: that run's most common answer was the overall favourite. Hollow cells: it was something else (normal for prompts with many good answers).

PromptMost common answers (share of all responses)Last 24 runsMedian tokens
Pick a random integer between 1 and 50. Reply with only the number.
int50 · short answer
69%37
31%27
23
Pick a number between 1 and 1000. Reply with only the number.
int1000 · short answer
78%537
10%637
5%437
8 distinct answers in 80 responses
20
Name one color. Reply with one word.
color · short answer
100%Blue
18
Name one animal. Reply with one word.
animal · short answer
90%Otter
6%Cat
4%Elephant
18
Name a city in Europe. Reply with only the city name.
city · short answer
69%Paris
28%Lisbon
1%Vienna
5 distinct answers in 80 responses
21
Give me one random English noun. Reply with one word.
noun · short answer
100%Lantern
25
Flip a coin. Reply with only heads or tails.
coin · short answer
96%heads
4%tails
19
Pick a random letter of the alphabet. Reply with only the letter.
letter · short answer
59%M
41%Q
20
Name one fruit. Reply with one word.
fruit · short answer
85%Apple
15%Mango
18
Suggest a name for a pet cat. Reply with only the name.
cat · short answer
95%Mochi
5%Miso
25
Name one programming language. Reply with only its name.
lang · short answer
100%Python
16
Name a chemical element. Reply with one word.
element · short answer
96%Oxygen
1%Carbon
1%Helium
4 distinct answers in 80 responses
20
Give one adjective that describes the ocean. Reply with one word.
ocean · short answer
100%Vast
24
Name a famous scientist. Reply with only the name.
scientist · short answer
85%Albert Einstein
15%Marie Curie
23
Pick a day of the week. Reply with one word.
weekday · short answer
46%Tuesday
46%Wednesday
8%Thursday
18
Name one musical instrument. Reply with one word.
instrument · short answer
78%Piano
19%Violin
3%Guitar
4 distinct answers in 80 responses
19
Write one sentence about rain.
rain · free text
63%Rain tapped softly against the…
13%Rain pattered softly against the…
9%Rain tapped gently against the…
11 distinct answers in 80 responses
34
Explain what a variable is in programming, in two sentences.
variable · free text
100%A variable is a named…
49
List three uses for a brick.
brick · free text
90%1. Building walls 2. Paving…
10%- Building walls - Paving…
42
What is 17 * 23?
mult · free text
70%17 × 23 = 391…
28%391…
3%17 × 23 = **391**…
26
Write one sentence about the sea.
sea · free text
94%The sea shimmered beneath the…
3%The sea whispered against the…
3%The sea rolled beneath the…
4 distinct answers in 80 responses
37
Complete this sentence: The old house at the end of the street
house · free text
100%The old house at the…
71
Describe a cat in exactly five words.
catfive · free text
43%A curious cat naps peacefully…
13%Soft paws, bright eyes, curious…
8%Soft paws, bright eyes, purring…
21 distinct answers in 80 responses
44
Give me a one-line motivational quote.
quote · free text
38%“Small steps taken consistently can…
11%“Small steps taken with courage…
6%“Keep moving forward—every small step…
20 distinct answers in 80 responses
38
Say hello in a creative way, in one short sentence.
hello · free text
13%Hello from the bright side…
9%Greetings from the bright side…
4%Greetings, earthling—may your day sparkle…
46 distinct answers in 80 responses
13
Write a haiku about autumn.
haiku · free text
55%Red leaves drift softly Cool…
13%Amber leaves drift down Cool…
8%Gold leaves drift softly Cool…
16 distinct answers in 80 responses
133
Write the first sentence of a mystery novel.
story · free text
11%By the time the lighthouse…
5%The first clue that my…
5%By the time the train…
49 distinct answers in 80 responses
65
Give one tip for sleeping better, in one sentence.
tip · free text
98%Keep a consistent bedtime and…
3%Keep your bedroom cool, dark…
31

Raw file: gpt-6-luna.json (the same reference martingale check compares your endpoint against).

Each category is scored by deterministic checks only (Structured JSON, Tool calling and others). Read the methodology.