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<div class="header-banner topBanner" data-type="header" style="display: block; position: sticky; top: 0; z-index: 999;">
<a data-source="226604" data-banner="226288" class="universal-notice js-universal-notice-notice universal-notice--webp universal-notice--bitrix universal-notice--active" href="https://skillbox.ru/sale/main/?utm_source=media&utm_medium=banners&utm_campaign=all_all_media_banners_banners_header_all_all_skillbox" target="_blank" style="--banner-bg: #5927E9;--banner-color: #fff;--button-font-color: #000000;--button-bg-color: #FFFFFF;--banner-img-left: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_left/602754/f9ac17dd-a1d4-46c6-aa14-4f7b949defd1.png);--banner-img-left-webp: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_left/602754/f9ac17dd-a1d4-46c6-aa14-4f7b949defd1.webp);--banner-img-center: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_center/602507/232fc4a5-b130-4af2-a629-bdb293a4dd2e.png);--banner-img-center-webp: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_center/602507/232fc4a5-b130-4af2-a629-bdb293a4dd2e.webp);--banner-img-center-mobile: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_center/602507/232fc4a5-b130-4af2-a629-bdb293a4dd2e.png);--banner-img-center-mobile-webp: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_center/602507/232fc4a5-b130-4af2-a629-bdb293a4dd2e.webp);--banner-img-right: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_right/602755/ad7a7fe5-b8d3-47a3-885b-51a7971c12a9.png);--banner-img-right-webp: url(https://cdn.skillbox.pro/mainsite/banners/promo_picture_right/602755/ad7a7fe5-b8d3-47a3-885b-51a7971c12a9.webp);">
<span class="universal-notice__wrapper">
<b class="universal-notice__title">
Скидка до 55% и 3 курса в подарок
</b>
<span class="universal-timer js-universal-notice-timer js-universal-notice-active">
<span class="universal-timer__days js-universal-notice-days">2 дня</span>
<span class="js-universal-notice-hours">13</span>
:<span class="js-universal-notice-minutes">30</span>
:<span class="js-universal-notice-seconds">09</span>
</span>
<span class="universal-notice__button">Выбрать курс</span>
</span>
</a><script>
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deadline.setDate(5);
deadline.setHours(0, 0, 0);
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const elHours = timer.querySelector('.js-universal-notice-hours');
const elMinutes = timer.querySelector('.js-universal-notice-minutes');
const elSeconds = timer.querySelector('.js-universal-notice-seconds');
// Функция обновления таймера
const updateTimer = () => {
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let diff = Math.max(0, deadline - now);
if (diff === 0) {
let lastDayOfMonth = new Date(now.getFullYear(), now.getMonth() + 1, 0);
let lastDay = lastDayOfMonth.getDate();
if (lastDay - now.getDate() < 4) {
deadline.setMonth(deadline.getMonth() + 1, 1);
} else {
deadline.setDate(deadline.getDate() + 4);
}
diff = Math.max(0, deadline - now);
}
// Time calculations for days, hours, minutes and seconds
var days = Math.floor(diff / (1000 * 60 * 60 * 24));
var hours = Math.floor((diff % (1000 * 60 * 60 * 24)) / (1000 * 60 * 60)).toString();
var minutes = Math.floor((diff % (1000 * 60 * 60)) / (1000 * 60)).toString();
var seconds = Math.floor((diff % (1000 * 60)) / 1000).toString();
if (timer) {
let dayTitles = ['день', 'дня', 'дней'];
let daySuffix = dayTitles[(days % 100 > 4 && days % 100 < 20) ? 2 : [2, 0, 1, 1, 1, 2][days % 10 < 5 ? days % 10 : 5]]
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elMinutes.innerHTML = minutes.padStart(2, '0');
elSeconds.innerHTML = seconds.padStart(2, '0');
}
};
updateTimer();
const timerId = setInterval(updateTimer, 1000);
});
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Редакция «Код» Skillbox Media </div>
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Онлайн-журнал для тех, кто влюблён в код и информационные технологии. Пишем для айтишников и об айтишниках. </div>
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<div class="stk-post stk-layout_12col_18068 stk-theme_26309" data-stk="{"images":[{"id":135458,"alt":"","caption":""}]}" data-ui-id="post" data-ce-tag="post" data-reset-type="class" data-layout-type="auto" data-editor-version="3.2.8-rc1"><div class="stk-grid" data-ce-tag="grid"><div data-col-width="12" class="stk-grid-col stk-grid-col_last" data-ce-tag="grid-col"><p class="stk-reset" data-ce-tag="paragraph">OpenAI <a href="https://openai.com/index/introducing-gpt-5-3-codex-spark/" target="_blank" class="stk-reset">выпустила</a> новую версию модели для разработчиков GPT-5.3-Codex-Spark. Её главное отличие от «рассуждающих» нейросетей компании — работа в реальном времени с большим контекстным окном, что позволяет сохранить точность при максимальной скорости генерации кода.</p><p class="stk-theme_26309__mb_15 stk-reset" data-ce-tag="paragraph">Попробовать GPT-5.3-Codex-Spark уже могут пользователи с подпиской ChatGPT Pro — например, в приложении Codex, терминале или IDE-плагинах.</p><h2 class="stk-theme_26309__style_large_header stk-reset" data-ce-tag="paragraph"><strong class="stk-reset">Что нового в GPT-5.3-Codex-Spark</strong></h2><p class="stk-theme_26309__mb_05 stk-reset" data-ce-tag="paragraph"><strong class="stk-reset">GPT-5.3-Codex-Spark </strong>— быстрая версия модели для программистов, дополняющая GPT-5.3-Codex, рассчитанную на автономные задачи. Её ключевые особенности:</p><ul class="stk-theme_26309__pad_hor_1 stk-reset" data-ce-tag="list"><li class="stk-reset stk-list-item" data-ce-tag="list-item"><strong class="stk-reset">высокая скорость генерации</strong> — Codex-Spark выдаёт более тысячи токенов в секунду, почти мгновенно реагируя на запросы и правки кода;</li><li class="stk-reset stk-list-item" data-ce-tag="list-item"><strong class="stk-reset">использование нового чипа</strong> — модель работает не на обычных графических процессорах NVIDIA, а на специализированных ускорителях <a class="stk-reset" href="https://www.cerebras.ai/chip" target="_blank">Cerebras Wafer Scale Engine 3</a>, что увеличивает пропускную способность и снижает задержки;</li><li class="stk-reset stk-list-item" data-ce-tag="list-item"><strong class="stk-reset">интерактивный режим взаимодействия</strong> — модель спроектирована так, чтобы пользователь мог сразу менять запросы, получать обновления кода и продолжать работу без пауз, как с живым коллегой;</li><li class="stk-reset stk-list-item" data-ce-tag="list-item"><strong class="stk-reset">меньший размер, высокая эффективность</strong> — Spark легче и быстрее, чем флагманская GPT-5.3-Codex, но при этом остаётся достаточно мощной моделью для решения реальных задач разработчиков.</li></ul><p class="stk-theme_26309__mb_15 stk-reset" data-ce-tag="paragraph">Эти изменения делают Codex-Spark особенно полезной там, где важна скорость отклика и внесения изменений — например при правке существующего кода и быстрой проверке гипотез прямо во время разработки.</p><h2 class="stk-theme_26309__style_large_header stk-reset" data-ce-tag="paragraph"><strong class="stk-reset">Что показывают бенчмарки</strong></h2><p class="stk-theme_26309__mb_05 stk-reset" data-ce-tag="paragraph">Результаты моделей на стандартизированных тестах помогают понять, насколько хорошо они справляются с практическими задачами. Для Codex-Spark OpenAI приводит такие оценки:</p><ul class="stk-theme_26309__pad_hor_1 stk-reset" data-ce-tag="list"><li class="stk-reset stk-list-item" data-ce-tag="list-item">на <strong class="stk-reset">SWE-Bench Pro</strong> — бенчмарке, оценивающем реальные задачи программирования на нескольких языках, — Spark набирает около 52%, тогда как старшая GPT-5.3-Codex показывает примерно 57%;</li><li class="stk-reset stk-list-item" data-ce-tag="list-item">на <strong class="stk-reset">Terminal-Bench 2.0</strong> — тесте навыков работы в терминале и при решении интерактивных задач — Spark показывает около 58,4%, что ниже, чем у флагманской версии (~77,3%), но выше, чем у предыдущих мини-версий моделей.</li></ul><p class="stk-reset" data-ce-tag="paragraph">Бенчмарки показывают, что Codex-Spark позволяет решать задачи разработчиков на приемлемом уровне, схожем с уровнем размышляющих моделей. При этом делает она это быстрее.</p><figure class="stk-reset stk-image-figure" data-ce-tag="image-figure"><div class="stk-mask" data-ce-tag="mask"><img src="/upload/setka_images/16340413022026_58d82a37db5372ff133658a2a59636cc9035941f.png" data-image-id="135458" data-image-name="1 (1).png" width="1540" height="1155" loading="lazy" class="stk-image stk-reset"/></div><figcaption style="display:block" class="stk-reset stk-description" data-ce-tag="description">Результаты GPT-5.3-Codex-Spark в SWE-Bench Pro: быстрее аналогичных моделей, но с меньшей точностью<br><em class="stk-reset">Изображение: OpenAI</em></figcaption></figure><div class="stk-grid stk-grid__layout_columns stk-theme_26309__mb_15" data-stk-css="stkDrHUd" data-ce-tag="grid"><div data-col-width="1" class="stk-grid-col align-left valign-top stk-mobile-hidden" data-ce-tag="grid-col" data-stk-css="" data-stk-css-m=""><a class="sklbx-link sklbx-link--fb stk-container stk-container-link stk-reset" data-ce-tag="container" data-container-name="Telegram" href="https://t.me/skillbox_media_code" target="_blank"><svg class="sklbx-link__icon" width="25" height="20" xmlns="http://www.w3.org/2000/svg">
<path d="m9.417 15.181-.397 5.584c.568 0 .814-.244 1.109-.537l2.663-2.545 5.518 4.041c1.012.564 1.725.267 1.998-.931l3.622-16.972.001-.001c.321-1.496-.541-2.081-1.527-1.714l-21.29 8.151c-1.453.564-1.431 1.374-.247 1.741l5.443 1.693 12.643-7.911c.595-.394 1.136-.176.691.218z" fill-rule="evenodd"></path>
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{"@context":"http:\/\/schema.org","@type":"Article","url":"https:\/\/skillbox.ru\/media\/code\/openai-predstavila-gpt-53-codex-spark-prodvinutuyu-model-dlya-programmistov\/","headline":"OpenAI \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b\u0430 GPT-5.3-Codex-Spark\u00a0\u2014 \u043f\u0440\u043e\u0434\u0432\u0438\u043d\u0443\u0442\u0443\u044e \u043c\u043e\u0434\u0435\u043b\u044c \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0441\u0442\u043e\u0432","articleSection":"\u041a\u043e\u0434","articleBody":"OpenAI \u0432\u044b\u043f\u0443\u0441\u0442\u0438\u043b\u0430 \r\n\u043d\u043e\u0432\u0443\u044e \u0432\u0435\u0440\u0441\u0438\u044e \u043c\u043e\u0434\u0435\u043b\u0438 \u0434\u043b\u044f \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0447\u0438\u043a\u043e\u0432 GPT-5.3-Codex-Spark. \u0415\u0451 \u0433\u043b\u0430\u0432\u043d\u043e\u0435 \u043e\u0442\u043b\u0438\u0447\u0438\u0435 \u043e\u0442 \u00ab\u0440\u0430\u0441\u0441\u0443\u0436\u0434\u0430\u044e\u0449\u0438\u0445\u00bb \u043d\u0435\u0439\u0440\u043e\u0441\u0435\u0442\u0435\u0439 \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0438 \u2014 \u0440\u0430\u0431\u043e\u0442\u0430 \u0432 \u0440\u0435\u0430\u043b\u044c\u043d\u043e\u043c \u0432\u0440\u0435\u043c\u0435\u043d\u0438 \u0441 \u0431\u043e\u043b\u044c\u0448\u0438\u043c \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442\u043d\u044b\u043c \u043e\u043a\u043d\u043e\u043c, \u0447\u0442\u043e \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0441\u043e\u0445\u0440\u0430\u043d\u0438\u0442\u044c \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c \u043f\u0440\u0438 \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0439 \u0441\u043a\u043e\u0440\u043e\u0441\u0442\u0438 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438 \u043a\u043e\u0434\u0430.\r\n\r\n\u041f\u043e\u043f\u0440\u043e\u0431\u043e\u0432\u0430\u0442\u044c GPT-5.3-Codex-Spark \u0443\u0436\u0435 \u043c\u043e\u0433\u0443\u0442 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u0438 \r\n\u0441 \u043f\u043e\u0434\u043f\u0438\u0441\u043a\u043e\u0439 ChatGPT Pro \u2014 \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0432 \u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u0438 Codex, \u0442\u0435\u0440\u043c\u0438\u043d\u0430\u043b\u0435 \u0438\u043b\u0438 IDE-\u043f\u043b\u0430\u0433\u0438\u043d\u0430\u0445.\u0427\u0442\u043e \u043d\u043e\u0432\u043e\u0433\u043e \u0432 GPT-5.3-Codex-Spark\r\n\r\nGPT-5.3-Codex-Spark \u2014 \u0431\u044b\u0441\u0442\u0440\u0430\u044f \u0432\u0435\u0440\u0441\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0438 \u0434\u043b\u044f \r\n\u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0441\u0442\u043e\u0432, \u0434\u043e\u043f\u043e\u043b\u043d\u044f\u044e\u0449\u0430\u044f GPT-5.3-Codex, \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u043d\u043d\u0443\u044e \u043d\u0430 \u0430\u0432\u0442\u043e\u043d\u043e\u043c\u043d\u044b\u0435 \u0437\u0430\u0434\u0430\u0447\u0438. \u0415\u0451 \u043a\u043b\u044e\u0447\u0435\u0432\u044b\u0435 \u043e\u0441\u043e\u0431\u0435\u043d\u043d\u043e\u0441\u0442\u0438:\r\n\r\n- \u0432\u044b\u0441\u043e\u043a\u0430\u044f \u0441\u043a\u043e\u0440\u043e\u0441\u0442\u044c \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0438 \u2014 Codex-Spark \r\n\u0432\u044b\u0434\u0430\u0451\u0442 \u0431\u043e\u043b\u0435\u0435 \u0442\u044b\u0441\u044f\u0447\u0438 \u0442\u043e\u043a\u0435\u043d\u043e\u0432 \u0432 \u0441\u0435\u043a\u0443\u043d\u0434\u0443, \u043f\u043e\u0447\u0442\u0438 \u043c\u0433\u043d\u043e\u0432\u0435\u043d\u043d\u043e \u0440\u0435\u0430\u0433\u0438\u0440\u0443\u044f \u043d\u0430 \u0437\u0430\u043f\u0440\u043e\u0441\u044b \u0438 \u043f\u0440\u0430\u0432\u043a\u0438 \u043a\u043e\u0434\u0430;\r\n- \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043d\u043e\u0432\u043e\u0433\u043e \u0447\u0438\u043f\u0430 \u2014 \u043c\u043e\u0434\u0435\u043b\u044c \r\n\u0440\u0430\u0431\u043e\u0442\u0430\u0435\u0442 \u043d\u0435 \u043d\u0430 \u043e\u0431\u044b\u0447\u043d\u044b\u0445 \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u0430\u0445 NVIDIA, \u0430 \u043d\u0430 \u0441\u043f\u0435\u0446\u0438\u0430\u043b\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0443\u0441\u043a\u043e\u0440\u0438\u0442\u0435\u043b\u044f\u0445 Cerebras Wafer Scale Engine 3 , \u0447\u0442\u043e \u0443\u0432\u0435\u043b\u0438\u0447\u0438\u0432\u0430\u0435\u0442 \u043f\u0440\u043e\u043f\u0443\u0441\u043a\u043d\u0443\u044e \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u043e\u0441\u0442\u044c \u0438 \u0441\u043d\u0438\u0436\u0430\u0435\u0442 \u0437\u0430\u0434\u0435\u0440\u0436\u043a\u0438;\r\n- \u0438\u043d\u0442\u0435\u0440\u0430\u043a\u0442\u0438\u0432\u043d\u044b\u0439 \u0440\u0435\u0436\u0438\u043c \u0432\u0437\u0430\u0438\u043c\u043e\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u044f \u2014 \r\n\u043c\u043e\u0434\u0435\u043b\u044c \u0441\u043f\u0440\u043e\u0435\u043a\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0430 \u0442\u0430\u043a, \u0447\u0442\u043e\u0431\u044b \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044c \u043c\u043e\u0433 \u0441\u0440\u0430\u0437\u0443 \u043c\u0435\u043d\u044f\u0442\u044c \u0437\u0430\u043f\u0440\u043e\u0441\u044b, \u043f\u043e\u043b\u0443\u0447\u0430\u0442\u044c \u043e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u044f \u043a\u043e\u0434\u0430 \u0438 \u043f\u0440\u043e\u0434\u043e\u043b\u0436\u0430\u0442\u044c \u0440\u0430\u0431\u043e\u0442\u0443 \u0431\u0435\u0437 \u043f\u0430\u0443\u0437, \u043a\u0430\u043a \u0441 \u0436\u0438\u0432\u044b\u043c \u043a\u043e\u043b\u043b\u0435\u0433\u043e\u0439;\r\n- \u043c\u0435\u043d\u044c\u0448\u0438\u0439 \u0440\u0430\u0437\u043c\u0435\u0440, \u0432\u044b\u0441\u043e\u043a\u0430\u044f \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u044c \u2014 \r\nSpark \u043b\u0435\u0433\u0447\u0435 \u0438 \u0431\u044b\u0441\u0442\u0440\u0435\u0435, \u0447\u0435\u043c \u0444\u043b\u0430\u0433\u043c\u0430\u043d\u0441\u043a\u0430\u044f GPT-5.3-Codex, \u043d\u043e \u043f\u0440\u0438 \u044d\u0442\u043e\u043c \u043e\u0441\u0442\u0430\u0451\u0442\u0441\u044f \u0434\u043e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u043e \u043c\u043e\u0449\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u044c\u044e \u0434\u043b\u044f \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u0440\u0435\u0430\u043b\u044c\u043d\u044b\u0445 \u0437\u0430\u0434\u0430\u0447 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0447\u0438\u043a\u043e\u0432.\r\n\r\n\u042d\u0442\u0438 \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u044f \u0434\u0435\u043b\u0430\u044e\u0442 Codex-Spark \u043e\u0441\u043e\u0431\u0435\u043d\u043d\u043e \u043f\u043e\u043b\u0435\u0437\u043d\u043e\u0439 \r\n\u0442\u0430\u043c, \u0433\u0434\u0435 \u0432\u0430\u0436\u043d\u0430 \u0441\u043a\u043e\u0440\u043e\u0441\u0442\u044c \u043e\u0442\u043a\u043b\u0438\u043a\u0430 \u0438 \u0432\u043d\u0435\u0441\u0435\u043d\u0438\u044f \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u0439 \u2014 \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440 \u043f\u0440\u0438 \u043f\u0440\u0430\u0432\u043a\u0435 \u0441\u0443\u0449\u0435\u0441\u0442\u0432\u0443\u044e\u0449\u0435\u0433\u043e \u043a\u043e\u0434\u0430 \u0438 \u0431\u044b\u0441\u0442\u0440\u043e\u0439 \u043f\u0440\u043e\u0432\u0435\u0440\u043a\u0435 \u0433\u0438\u043f\u043e\u0442\u0435\u0437 \u043f\u0440\u044f\u043c\u043e \u0432\u043e \u0432\u0440\u0435\u043c\u044f \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0438.\u0427\u0442\u043e \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u044e\u0442 \u0431\u0435\u043d\u0447\u043c\u0430\u0440\u043a\u0438\r\n\r\n\u0420\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u044b \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \r\n\u0442\u0435\u0441\u0442\u0430\u0445 \u043f\u043e\u043c\u043e\u0433\u0430\u044e\u0442 \u043f\u043e\u043d\u044f\u0442\u044c, \u043d\u0430\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0445\u043e\u0440\u043e\u0448\u043e \u043e\u043d\u0438 \u0441\u043f\u0440\u0430\u0432\u043b\u044f\u044e\u0442\u0441\u044f \u0441 \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u0437\u0430\u0434\u0430\u0447\u0430\u043c\u0438. \u0414\u043b\u044f Codex-Spark OpenAI \u043f\u0440\u0438\u0432\u043e\u0434\u0438\u0442 \u0442\u0430\u043a\u0438\u0435 \u043e\u0446\u0435\u043d\u043a\u0438:\r\n\r\n- \u043d\u0430 SWE-Bench Pro \u2014 \u0431\u0435\u043d\u0447\u043c\u0430\u0440\u043a\u0435, \u043e\u0446\u0435\u043d\u0438\u0432\u0430\u044e\u0449\u0435\u043c \r\n\u0440\u0435\u0430\u043b\u044c\u043d\u044b\u0435 \u0437\u0430\u0434\u0430\u0447\u0438 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u0430 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u044f\u0437\u044b\u043a\u0430\u0445, \u2014 Spark \u043d\u0430\u0431\u0438\u0440\u0430\u0435\u0442 \u043e\u043a\u043e\u043b\u043e 52%, \u0442\u043e\u0433\u0434\u0430 \u043a\u0430\u043a \u0441\u0442\u0430\u0440\u0448\u0430\u044f GPT-5.3-Codex \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442 \u043f\u0440\u0438\u043c\u0435\u0440\u043d\u043e 57%;\r\n- \u043d\u0430 Terminal-Bench 2.0 \u2014 \u0442\u0435\u0441\u0442\u0435 \u043d\u0430\u0432\u044b\u043a\u043e\u0432 \u0440\u0430\u0431\u043e\u0442\u044b \r\n\u0432 \u0442\u0435\u0440\u043c\u0438\u043d\u0430\u043b\u0435 \u0438 \u043f\u0440\u0438 \u0440\u0435\u0448\u0435\u043d\u0438\u0438 \u0438\u043d\u0442\u0435\u0440\u0430\u043a\u0442\u0438\u0432\u043d\u044b\u0445 \u0437\u0430\u0434\u0430\u0447 \u2014 Spark \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442 \u043e\u043a\u043e\u043b\u043e 58,4%, \u0447\u0442\u043e \u043d\u0438\u0436\u0435, \u0447\u0435\u043c \u0443 \u0444\u043b\u0430\u0433\u043c\u0430\u043d\u0441\u043a\u043e\u0439 \u0432\u0435\u0440\u0441\u0438\u0438 (~77,3%), \u043d\u043e \u0432\u044b\u0448\u0435, \u0447\u0435\u043c \u0443 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 \u043c\u0438\u043d\u0438-\u0432\u0435\u0440\u0441\u0438\u0439 \u043c\u043e\u0434\u0435\u043b\u0435\u0439.\r\n\r\n\u0411\u0435\u043d\u0447\u043c\u0430\u0440\u043a\u0438 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u044e\u0442, \u0447\u0442\u043e Codex-Spark \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \r\n\u0440\u0435\u0448\u0430\u0442\u044c \u0437\u0430\u0434\u0430\u0447\u0438 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0447\u0438\u043a\u043e\u0432 \u043d\u0430 \u043f\u0440\u0438\u0435\u043c\u043b\u0435\u043c\u043e\u043c \u0443\u0440\u043e\u0432\u043d\u0435, 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