GPT-6 Luna
OpenAIKey gpt-6-lunaAlso reported as main/gpt-6-luna, sub2api-codex/gpt-6-luna, openai/gpt-6-luna, cx/gpt-6-luna, codex/gpt-6-luna, p2d5835/gpt-6-luna, p89007d/gpt-6-luna, rmagpie/codex/gpt-6-luna, gh/gpt-6-luna, router_client:unknown/gpt-6-luna, nfq5kbw/gpt-6-luna, openai-codex/gpt-6-luna, workbuddy-ai/gpt-6-luna, cb/gpt-6-luna, router_client:codex/gpt-6-luna, opencode-go/gpt-6-luna, router_client:claude/gpt-6-luna, command-code/gpt-6-luna, combo/gpt-6-luna
- Rank
- #7
- by active users
- Active users
- 154
- Down 65 from 219 active users in the previous 7 days. vs previous 7 days
- Adoption
- 25%
- of 610 accounts
- Tokens
- 95.8B
- cache included
- Est. cost
- $1.8K
- at public list prices
- First seen
- Jul 7, 2026
- in any submission
Nov 6–12, 2026 (UTC)610 accounts100% of tokens from an identified modelData through Nov 12, 2026, 08:00 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
26 active users on Nov 12, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Nov 6, 2026 | 89 | 10.4B |
| Nov 7, 2026 | 76 | 15.8B |
| Nov 8, 2026 | 59 | 20B |
| Nov 9, 2026 | 82 | 18.5B |
| Nov 10, 2026 | 74 | 17.9B |
| Nov 11, 2026 | 49 | 10.5B |
| Nov 12, 2026 | 26 | 3.2B |
Token mix
How the 95.8B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input6.3%
- Output0.2%
- Cache read93%
- Cache write<0.1%
- Reasoning0.2%
Agents that carry GPT-6 Luna
Each agent's share of this model's tokens, and how many accounts used the model through it.
Codex CLI81% of this model's tokens97active users
Junie14% of this model's tokens1active users
Senpi (OmO Native)1.6% of this model's tokens15active users
Oh My Pi1.1% of this model's tokens12active users
OpenCode0.8% of this model's tokens10active users
Hermes Agent0.4% of this model's tokens18active users
Pi0.4% of this model's tokens8active users
Gajae Code<0.1% of this model's tokens3active users
Aside<0.1% of this model's tokens10active users
Claude Code<0.1% of this model's tokens1active users
DeepSeek Harness<0.1% of this model's tokens1active users
Hindsight<0.1% of this model's tokens1active users
Reasonix<0.1% of this model's tokens1active users
Copilot<0.1% of this model's tokens1active users- cc-mirror/curl<0.1% of this model's tokens1active users
Droid<0.1% of this model's tokens1active users
Zed Agent<0.1% of this model's tokens1active users- cc-mirror/mozilla<0.1% of this model's tokens1active users
Benchmarks
The best result for GPT-6 Luna in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark. Agent rows also show Tokscale usage through that agent, side by side with the score. Usage does not explain the score.
- Epoch Capabilities IndexOverall · Epoch AI156.4
Epoch Capabilities Index: 156.4
- Model
- GPT-6 Luna
- Listed as
- GPT-6 Luna
- Conditions
- Not reported
- Interval
- 154.4–158.5
- Unit
- ECI
- Model released
- Sep 22, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #36 of 158 matched modelsNo conditions reportedModel released Sep 22, 2026Source: epoch.ai (opens in a new tab) - Terminal-Bench 4.1Agentic coding · Terminal-Bench15.2%
Terminal-Bench 4.1: 15.2%
- Model
- GPT-6 Luna
- Listed as
- GPT-6 Luna
- Conditions
- Max · Codex
- Interval
- 12.5–17.8%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
Tokscale usage: Codex CLI carried 81% of GPT-6 Luna tokens in the last 7 days (97 active users). - WebDev ArenaWeb development · LMArena1,578
WebDev Arena: 1,578
- Model
- GPT-6 Luna
- Listed as
- GPT-6 Luna (Max)
- Conditions
- Max
- Interval
- 1572–1584
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
- Agent ArenaAgents · LMArena+0.03
Agent Arena: +0.03
- Model
- GPT-6 Luna
- Listed as
- GPT-6 Luna (Max)
- Conditions
- Max · Arena Agent Mode
- Interval
- 0.02 to 0.03
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Best of 2 reported results for this model.
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #18 of 48 matched modelsMax · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab)Show 1 more result with other run conditionsHide the other results
- Listed as GPT-6 Luna (Low)−0.05
Agent Arena: −0.05
- Model
- GPT-6 Luna
- Listed as
- GPT-6 Luna (Low)
- Conditions
- Low · Arena Agent Mode
- Interval
- -0.06 to -0.03
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
- GPQA DiamondReasoning · Epoch AI90.5%
GPQA Diamond: 90.5%
- Model
- GPT-6 Luna
- Listed as
- gpt-6-luna_max
- Conditions
- Max
- Unit
- % correct
- Run date
- Sep 22, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.
- FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI78.9%
FrontierMath Tiers 1–3 (v2): 78.9%
- Model
- GPT-6 Luna
- Listed as
- gpt-6-luna_max
- Conditions
- Max
- Unit
- % solved
- Run date
- Sep 22, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 95.1%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.
- SimpleQA VerifiedKnowledge · Epoch AI41.4%
SimpleQA Verified: 41.4%
- Model
- GPT-6 Luna
- Listed as
- gpt-6-luna_max
- Conditions
- Max
- Unit
- % correct
- Run date
- Sep 22, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Pricing
List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. OpenAI is the lab's own API and the reference price for the estimates below.
Price at real agent usageEstimate at list prices
What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.
- At this model's mix
- $0.02
- Est. per 1M tokens
93% cache reads - At the community mix
- $0.02
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $0.20
- Per 1M tokens at list prices
No cache
Cache reads were 93% of GPT-6 Luna tokens in the last 7 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.
Assumptions
- OpenAI list prices per 1M tokens: input $0.10, output $0.50, cache read $0.01, cache write $0.13.
- This model's mix is its own input, output, cache and reasoning tokens in the last 7 days.
- The community mix is the tokens of every identified model in the last 7 days.
- This is an estimate at list prices, not what anyone paid.
- Reasoning tokens are priced as output.
- Long-context tiers, batch pricing and discounts are not applied.
- Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
List prices by provider
- OpenAIReference
gpt-6-luna$0.10 input per 1M tokens$0.50 output per 1M tokens$0.01 cache read per 1M tokens$0.13 cache write per 1M tokens1.05M tokens of context - Amazon Bedrock
openai.gpt-6-luna$0.11 input per 1M tokens$0.55 output per 1M tokens$0.01 cache read per 1M tokens$0.14 cache write per 1M tokens1.05M tokens of context - Azure
gpt-6-luna$0.10 input per 1M tokens$0.50 output per 1M tokens$0.01 cache read per 1M tokens$0.13 cache write per 1M tokens1.05M tokens of context - OpenRouter
openai/gpt-6-luna$0.10 input per 1M tokens$0.50 output per 1M tokens$0.01 cache read per 1M tokens$0.13 cache write per 1M tokens1.05M tokens of context - Vercel AI Gateway
openai/gpt-6-luna$0.10 input per 1M tokens$0.50 output per 1M tokens$0.01 cache read per 1M tokens$0.13 cache write per 1M tokens1.05M tokens of context
Specs
From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.
- Context window
- 1.05M tokens
- Max output
- 128K tokens
- Input
- Text, Image, PDF
- Output
- Text
- Knowledge cutoff
- May 18, 2026
- Release date
- Sep 22, 2026
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used GPT-6 Luna most in this period, by tokens. Hidden accounts are never listed.
- 1
Shun Kakinoki@shunkakinoki50.6Btokens$964est. cost7active days$964 est. cost · 7 active days
- 2
ualtinok@ualtinok13.7Btokens$396est. cost7active days$396 est. cost · 7 active days
- 3
Seungwoo Ryu@ryuryu106.3Btokens$80est. cost7active days$80 est. cost · 7 active days
- 4
Azest Kingscrown@azestkingscrown3.5Btokens$41est. cost3active days$41 est. cost · 3 active days
- 5
drscorpion7@drscorpion73.2Btokens$41est. cost5active days$41 est. cost · 5 active days
- 6
Carlos Florêncio@carlosflorencio2.5Btokens$35est. cost6active days$35 est. cost · 6 active days
- 7
ManzJoozy@JTZ182.1Btokens$14est. cost7active days$14 est. cost · 7 active days
- 8
Juhwa Lee@Juhwa-Lee10231.7Btokens$27est. cost6active days$27 est. cost · 6 active days
- 9
jisongkun@jisongkun1.5Btokens$20est. cost6active days$20 est. cost · 6 active days
- 10
Lee Wai Chong@leewaichong1.1Btokens$25est. cost7active days$25 est. cost · 7 active days
More from OpenAI
Other OpenAI models in the same period, by active users.
- GPT-6.1 Sol57% adoption350active users
- GPT-6 Astra44% adoption268active users
- GPT-6.1 Terra22% adoption136active users
- Codex Auto Review18% adoption112active users
- GPT-5.6 Sol10% adoption61active users
- GPT-6 Sol8.7% adoption53active users
Sources and attribution
Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.