[whatmodel.sh](../../README.md) / GPT-6 Luna
# GPT-6 Luna
OpenAI · released 2026-09 · closed weights
**score 75.1** ±0.6 · #33 of 732 · from 22 benchmark results across 6 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks GPT-6 Luna among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄▅▅▄●▂▁ #28 of 313 17% 3
coding ▁▁▁▃▅▇█▇▅▄●▁ #37 of 469 12% 3
chat & writing ▁▁▁▃▆▄▆█▆▇●▃ #64 of 402* 4.1% 1
math ▁▁▃▅█▆▄█▄●▁▁ #18 of 431 35% 3
vision & documents ▁▁▂▂▁▃▄▂▆●█▄ #61 of 153* 2.7% 1
web search ▁▁▁▅▄●▃▄·▁·▁ #26 of 84* 1.5% 1
agent tasks · #28 of 313 · 17% of its score
Beats [Hy4 preview (770B-A49B)](hy4-preview.md), [GPT-5.6 Terra](gpt-5-6-terra.md), [Qwen3.8 Max (2.4T-A95B)](qwen3-8-2-4t-a95b.md) here, though they rank higher overall. Trails [Grok 4.7](grok-4-7.md), [GLM-5.3](glm-5-3.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena Agent (October 2026 aggrega… 0.0223 IPS ▁▁▁▃▃▂●▁▂▂▁▁ beats 36/59 avg -0.379 IPS 11% sharp
Terminal-Bench 4.0 16.4% █●▅▅▅·▅▃▃▅▅▅ beats 4/20 very hard · avg 0.5% 4.1% sharp
DeepSWE v1.1 (resolved) (maker) 66.6% ●··▃▃····▃·▃ beats 0/6 hard · avg 22% 2.2% at its level
coding · #37 of 469 · 12% of its score
Beats [GPT-5.5](gpt-5-5.md), [GPT-5.6 Terra](gpt-5-6-terra.md), [Claude Opus 4.8](claude-opus-4-8.md) here, though they rank higher overall. Trails [Qwen3.8 27B](qwen3-8-27b.md), [GLM-5.2](glm-5-2.md), [GLM-5.3-Flash](glm-5-3-flash.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena WebDev (Code Arena) 1579.4 ▁▁▃▂▅█▃▆●▅▁▂ beats 92/129 avg 981 7.3% sharp
Luau Leetcode fully solved (Torpe… 80.8% ▁▁▁▁·▁▂▃▅▃●▇ beats 34/49 hard · avg 17% 2.7% sharp
DeepSWE v1.1 (resolved) (maker) 66.6% ●··▃▃····▃·▃ beats 0/6 hard · avg 22% 2.2% at its level
chat & writing · #64 of 402 · 4.1% of its score
Beats [Claude Haiku 5.5](claude-haiku-5-5.md) here, though they rank higher overall. Trails [Nemotron Cascade 2 30B-A3B](nemotron-cascade-2-30b-a3b.md), [Gemma 4 31B](gemma-4-31b.md), [Gemini 2.5 Pro](gemini-2-5-pro.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1440.9 ▁▁▁▂▃▃▃▆▆▇●▃ beats 303/385 avg 1260 4.1% blunt
math · #18 of 431 · 35% of its score
Beats [DeepSeek V4.1 Flash 1017](deepseek-v4-1-flash-1017.md), [Qwen3.8 Max (2.4T-A95B)](qwen3-8-2-4t-a95b.md), [Claude Opus 4.8](claude-opus-4-8.md) here, though they rank higher overall. Trails [GPT-5.6 Luna](gpt-5-6-luna.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
FrontierMath tier 4 v2 56.1% ▁▂▁▂█▅●▃▂▁▁▁ beats 50/67 very hard · avg 0.1% 18% sharp · at its level
FrontierMath tiers 1–3 v2 78.9% ▂··▁▁▃▄▄█●▄▃ beats 69/86 very hard · avg 1.2% 17% sharp · at its level
OTIS mock AIME 2024–2025 98.9% ▃▃▄▃▃▃▇▇█▃▂● beats 179/197 very hard · avg 7.2% 0.5% sharp · maxed out · noisy
vision & documents · #61 of 153 · 2.7% of its score
Trails [Gemma 4 26B-A4B](gemma-4-26b-a4b.md), [Qwen3.6 Flash](qwen3-6-flash.md), [Qwen3.5 35B-A3B](qwen3-5-35b-a3b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena vision (style controlled) 1240.4 ▁▁▂▂▂▂▃▄▅▅●▇ beats 95/152 avg 1061 2.7% blunt
web search · #26 of 84 · 1.5% of its score
Beats [Claude Opus 4.8](claude-opus-4-8.md), [GPT-5.4](gpt-5-4.md), [Claude Haiku 5.5](claude-haiku-5-5.md) here, though they rank higher overall. Trails [GPT-4o mini (2024-07-18)](gpt-4o-mini-2024-07-18.md), [Mistral Small 3.1 24B (2503)](mistral-small-3-1.md), [GPT-4o (2024-08-06)](gpt-4o-2024-08-06.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena search systems (style contr… 1209.3 ▁·▁▁▂▂▂█●▃▂▂ beats 26/36 avg 1069 1.5% blunt
other tests (11)
test result vs the others in its run difficulty counts why
Furniture Assembly (Epoch) 44.2% █▆▆▆●▂▆▂▂▂▂▅ beats 19/32 very hard · avg 1.2% 7.1% sharp · at its level
Mystery Game Puzzles (Epoch) 7.0% ●··▂▃▇▄█▂▄▂▁ beats 0/77 very hard · avg 9.4% 7.0% sharp · at its level · noisy
Chess Puzzles (Epoch) 31.0% █▁▁▁▁▂▃▃●▂▁▁ beats 105/137 very hard · avg 5.8% 4.0% sharp · at its level · noisy
GPQA Diamond 90.5% ▁▁▁▁▂▄▆▄▅▇●▅ beats 176/211 hard · avg 39% 2.5% sharp
SimpleQA Verified 41.4% ▁▁▃▂▃▃▆●█▄▂▅ beats 38/81 very hard · avg 8.0% 1.6% at its level
Icelandic LLM Leaderboard average… 57.1% ▁▁▃▂▂▄▁▃▄●▄█ beats 25/38 very hard · avg 14% 1.5% at its level
HealthBench Professional (maker) 60.8% ▄·▄··▄▄·▄●·█ beats 5/8 hard · avg 20% 1.5% blunt · at its level
MirrorCode (Epoch) 26.7% ▄·█▄▄●██·▄▄█ beats 5/13 very hard · avg 1.6% 1.1% sharp · at its level · noisy
RobloxQA v2.0 multiple choice (To… 95.6% ▁▁▃▁█▄▃●▆▂▂▂ beats 30/49 easy · avg 77% 0.9% maxed out
HealthBench Hard (maker) 25.4% ▂··●····▂▄·█ beats 1/8 very hard · avg 9.6% 0.9% blunt · at its level
HealthBench (maker) 50.0% ▃·●·····█▃▃▅ beats 1/8 hard · avg 24% 0.9% blunt · at its level
source results share of the score
Epoch AI 9 59% ▇▇▇▇▇▇▇
LMArena leaderboard dataset 5 26% ▇▇▇
OpenAI vendor-reported benchmark scores… 4 6% ▇
Terminal-Bench 4.0 official leaderboard… 1 4% ▇
Roblox LLM Leaderboard 2 4% ▇
Miðeind Icelandic LLM Leaderboard 1 2% ▇
prior: pull toward the middle 0% ▇
weighted average = 75.1
Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Terminal-Bench 4.0 official leaderboard submissions ([Apache-2.0](../../licenses/terminal-bench-leaderboard-submissions-Apache-2.0.txt)) · Roblox LLM Leaderboard ([MIT](../../licenses/roblox-llm-leaderboard-MIT.txt)) · Miðeind Icelandic LLM Leaderboard ([CC BY 4.0](../../licenses/mideind-icelandic-llm-leaderboard-CC-BY-4.0.txt))
## How to run it
### Through an API
api (OpenAI) · $0.20/M blended · $0.1 in / $0.5 out per 1M tokens · [platform.openai.com](https://platform.openai.com/docs/models)
[price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/openai/models/gpt-6-luna.toml): Standard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ. · [context source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/models/openai/gpt-6-luna.toml)
[interactive version](https://whatmodel.sh/model/gpt-6-luna) · [JSON](https://whatmodel.sh/api?format=json&all=1)