gpt-6-luna vs gpt-6-sol

Parameters, independent leaderboard coverage, real-task reports and open-weight availability are shown side by side; missing coverage is not a zero.

Parameters

Comparison itemgpt-6-lunagpt-6-sol
Model TypeLLMLLM
Context window1,050,000 tokens1,050,000 tokens
Maximum output128,000 tokens128,000 tokens
Input/output modalitiestext, image → texttext, image → text
Endpointopenai · openai-responseopenai · openai-response
Open weightsUnavailableUnavailable
LicenseProprietary hosted modelProprietary hosted model

Leaderboard coverage

Every independent board covering either model is retained; an em dash means that board has not published a figure for that model.

Evaluationgpt-6-lunagpt-6-sol
Artificial Analysis Intelligence Index — Intelligence Index3748
Artificial Analysis · Output Speed — Median output tokens/s157104
Artificial Analysis · GDPval-AA v2.1 — Agentic Real-World Work Tasks, (Elo-500)/2000 (%)4349
Artificial Analysis · Terminal-Bench v4.0 — Agentic Coding & Terminal Use (%)1344

Real-task reports

gpt-6-luna

  • GPT-6 Astra, Sol and Luna on one SVG animation prompt — Generate an SVG animation of a pelican riding a bicycle, shown in H5. Finding: GPT-6 Luna was the quickest and lightest of the four at 2 min 18 s and 1% of the five-hour quota, but the author dismissed its result as a flop (“拉完了”), ranking it alongside MiMo-V2.6-Flash. Limitation: One prompt judged by the author without a score; the quota shares are a subscription meter, not API cost. X's automatic translation renders the verdict as its opposite, so read the original Chinese.

gpt-6-sol

  • Claude Opus 5.5 and GPT-6 Sol on one interactive website prompt — Build an interactive website about imaginary planets from a single prompt. Finding: GPT-6 Sol took 10 minutes and built three planets, using 1% of the $200 plan's usage; Claude Opus 5.5 took 26 minutes for a fuller, explorable solar system with more detail, using 16% of the $20 plan's usage. The author found the planets surprisingly similar: Sol faster, Opus bigger and more detailed. Limitation: One prompt judged by the author; the usage shares are meters of two different subscription plans, not API costs.
  • Four models build the Eiffel Tower in Three.js — Build the Eiffel Tower in Three.js. Finding: GPT-6 Sol was the cheapest and fastest of the four at $3.90 and 5 minutes, but the author found its result a bit disappointing; they preferred Claude Opus 5.5 ($8.95, 10 minutes) and rated Kimi K3 ($4.04, 6 minutes) strong for the price. Limitation: One task judged by eye by the author; the post does not say how the models were run or how the costs were counted.
  • Claude Pro, Codex Plus and SuperGrok on the same work at maximum settings — One piece of work run on each $20 subscription; the task itself is shown only in the author's video. Finding: GPT-6 Sol on Codex Plus used 9% of the weekly limit (29 million tokens) over 69 minutes and scored 7/10, the highest of the three plans, against 5/10 for Opus 5.5 and 6/10 for Grok 4.7; the author still recommends Claude at $20 because it yields far more tokens, and puts Codex Plus at about $330 of API usage a month. Limitation: The post does not describe the task, the quality score is the author's own, and the numbers are subscription meters rather than API usage.
  • GPT-6 Astra, Sol and Luna on one SVG animation prompt — Generate an SVG animation of a pelican riding a bicycle, shown in H5. Finding: GPT-6 Sol took 4 min 42 s and used 2% of the five-hour quota, against 6 min 3 s and 16% for GPT-6 Astra; the author puts Sol's quota use at an eighth of Astra's and recommends Sol when quota matters. Limitation: One prompt; the quota shares are a subscription meter, not API cost, and the post gives no quality score for Sol.