gpt-6-sol real-task evaluations

Every report keeps its original task, method, finding, limitation, evaluator identity and verification date. A community report is evidence about that run, not a universal score.

  • Claude Opus 5.5 and GPT-6 Sol on one interactive website prompt

    By Kappaemme (@Kappaemme1926). X user who posted this side-by-side test Published 2026-09-23; retrieved 2026-09-24; verified 2026-09-24.

    Task
    Build an interactive website about imaginary planets from a single prompt
    Method
    Same prompt with both models on High; the author reported wall-clock time, how much each result covered and the share of each subscription's usage.
    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

    By Bhavy (@Bhavani_00007). X user who ran the same Three.js task on four models and reported cost and time Published 2026-09-23; retrieved 2026-09-24; verified 2026-09-24.

    Task
    Build the Eiffel Tower in Three.js
    Method
    Same task on Claude Opus 5.5, GPT-6 Astra, GPT-6 Sol and Kimi K3; the author reported cost and time for each and compared the results by eye.
    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

    By shownotover (@shownotover). X user comparing $20 AI subscriptions in their first video Published 2026-09-24; retrieved 2026-09-24; verified 2026-09-24.

    Task
    One piece of work run on each $20 subscription; the task itself is shown only in the author's video
    Method
    Each plan's top model at maximum reasoning (Grok 4.7 at xhigh); the author recorded the share of the weekly limit, tokens, working time and a 1–10 quality score.
    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

    By 雪瑜 (@xueyu1125). Programmer and AI-tools builder on X who posted the timings and quota readings Published 2026-09-23; retrieved 2026-09-24; verified 2026-09-24.

    Task
    Generate an SVG animation of a pelican riding a bicycle, shown in H5
    Method
    Same prompt on GPT-6 Astra, GPT-6 Sol, GPT-6 Luna and GPT-5.6 Sol; the author recorded time taken and the share of a five-hour subscription quota each used.
    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.

  • Four models build a lava lamp from one prompt

    By Bridgebench (@bridgebench). BridgeMind's benchmark account, which calls itself the official AI benchmark of the vibe coding movement Published 2026-09-23; retrieved 2026-09-24; verified 2026-09-24.

    Task
    Build a lava lamp from a single prompt
    Method
    Same prompt on Claude Opus 5.5, GPT-6 Astra, GPT-6 Sol and GPT-6 Luna; the account reported cost and time, asked readers which did best and commented on their answers in replies.
    Finding
    GPT-6 Sol cost $0.08 and took 50 seconds, against $1.27 and 9 min 35 s for Claude Opus 5.5 and $0.63 and 5 min 4 s for GPT-6 Astra; in replies the account agreed Opus had a rough showing on this test.
    Limitation
    One prompt with the quality verdict left mostly to readers; the account is BridgeMind's own benchmark and does not say how the models were accessed.

  • Claude Opus 5.5 and GPT-6 Sol on a black hole merger test

    By Bridgebench (@bridgebench). BridgeMind's benchmark account, which calls itself the official AI benchmark of the vibe coding movement Published 2026-09-24; retrieved 2026-09-24; verified 2026-09-24.

    Task
    The account's black hole merger visualisation test
    Method
    The same test on both models; the account reported cost and time and judged the design.
    Finding
    GPT-6 Sol cost $0.08 and took 1 min 33 s, an eighth of Claude Opus 5.5's cost and four times faster, but the account judged Opus 5.5 'a significant leap for design. It's not close.'
    Limitation
    One test judged by the account; the task is shown only in the attached video.

  • Claude Opus 5.5 and GPT-6 Sol on one motion-graphic prompt

    By Hunter Bohm (@TheHunterBohm). Builds agent systems for business and posted a longer comparison video Published 2026-09-23; retrieved 2026-09-24; verified 2026-09-24.

    Task
    Make a 20-second motion graphic explaining how a language model turns a prompt into an answer and why long answers cost more
    Method
    Same prompt on both models; the author reported time and cost and posted the prompt and a full comparison video in replies.
    Finding
    GPT-6 Sol took 11.4 minutes and $1.09 against Claude Opus 5.5's 12.7 minutes and $2.86; the author called the gap 'not even close' and agreed with a reply that Sol's result was far worse.
    Limitation
    One subjective prompt; the verdict comes from the author's post and replies rather than a score.

  • GPT-6 Sol and GPT-6 Astra on a robot drawing benchmark

    By Dmytro Hrybov (@dimentary). ML research engineer working on physical learning and evaluations Published 2026-09-22; retrieved 2026-09-24; verified 2026-09-24.

    Task
    The author's robot-drawing-on-the-board benchmark
    Method
    The same benchmark on both models; the author compared output tokens, drawing speed and running cost.
    Finding
    GPT-6 Sol used about 25k output tokens against Astra's 22k and its controller drew twice as fast, at almost a fifth of the running cost; the author had expected stronger spatial reasoning from it.
    Limitation
    One run of a benchmark the post describes only by name, with no score.

  • AI Coding Daily LLM Coding Leaderboard

    By AI Coding Daily (@AICodingDaily). Coding-model testing channel and website that runs its own leaderboard and sells premium tutorials and channel advertising Published 2026-09-24; retrieved 2026-09-24; verified 2026-09-24.

    Task
    Implement and harden production-shaped projects in several stacks, including a Laravel app, a Go service and a React/TypeScript app, from the same prompts
    Method
    Each model and reasoning setting is a separate row run in a coding harness, with the average cost and time per run. Code quality is graded by a judge model against a published 100-point rubric and scaled to 20 points per project; behavioural reliability runs each of four projects five times and scores the checks every attempt fails.
    Finding
    GPT-6 Sol scored 52.42 at high reasoning ($0.31 and 5 min 18 s per run in Codex CLI) and 50.07 at medium, 8th and 16th of 47 rows; Claude Opus 5.5 led with 57.83 and GPT-6 Astra at medium scored 56.03.
    Limitation
    One author's benchmark whose code-quality half is graded by a judge model; rows run in different harnesses, the page is updated as models are added (read on 2026-09-24, 47 rows), and the author sells premium tutorials and advertising.

  • kzhu's six-question LLM test leaderboard

    By AI产品狙击手 kzhu (@kevinzhu9305). Chinese YouTube reviewer who scores models on a six-question test and publishes every score with per-question notes Published 2026-09-24; retrieved 2026-09-24; verified 2026-09-24.

    Task
    Six questions scored out of 10: constrained sentence writing, two reasoning puzzles (replaced by pelican and compound-bow SVG animations in version 2.2), a browser OS with a space shooter, a 3D racing game and a Trello-style board
    Method
    Each row names the harness the model ran in (Pi, Claude Code, WorkBuddy and others) and the date; the author scores every question with a note, and warns that totals are only comparable within one test version.
    Finding
    GPT-6 Sol scored 44/60 on version 2.2 in Pi: full marks on the constrained sentences, but SVG animations with reversed wheels and an arrow that broke physics (6 each), a space shooter that only moved sideways, and an English interface for a Chinese Trello brief; Claude Opus 5.5 scored 55 on the same version.
    Limitation
    One author's scores on six questions; rows use different harnesses and test versions (2.1 or 2.2), and a few rows' table total differs by one point from the author's note.