100 Hours Testing Deepseek Harness vs. Claude Code. What You Need to Know.
Nate Herk | AI Automation · 2026-08-23 · 18м 2с · 29 124 просмотров · YouTube ↗
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📝 Summary
model=deepseek-v4-flash · prompt=summary-v7 · 6 657→9 556 tokens · 2026-08-25 12:34:41
🎯 Главная суть
DeepSeek выпустила открытый агентный харнесс — бесплатный аналог Claude Code и Codex, который перекраивается под себя через плагины и принимает любые модели: от собственных DeepSeek V4 Flash и V4 Pro до Claude, GPT и Gemini через OpenRouter. На одинаковых задачах он стабильно быстрее Claude Code (в одном тесте — 3 минуты против 17), но пока ощущается как сырое превью: есть баги, слабый «дизайн-глаз» и менее консервативные выводы.
Что такое DeepSeek Harness
Это open-source агентный харнесс от DeepSeek — по назначению аналог Codex от OpenAI и Claude Code от Anthropic, но бесплатный и открытый. Внутри по умолчанию работают модели самой DeepSeek: V4 Flash — дешёвая и очень хорошая, V4 Pro — тоже сильная. Через OpenRouter или локальный запуск подключаются любые сторонние модели: Claude, GPT, Gemini и другие OpenAI-совместимые. Можно даже привязать существующую подписку Claude или Codex — тогда токены тарифицируются через неё, а без подписки расходы идут за инференс по API. Сам харнесс бесплатен: если использовать бесплатную модель, за использование харнесса платить не придётся. Интерфейс выглядит как привычный чат: сессии, управление проектами, переключение моделей. По сути это не прорывная технология, а именно новый открытый харнесс — и главная его фишка в том, что его можно разобрать до винтика.
Архитектура «всё — плагин»
Ключевое отличие от закрытых харнессов: буквально каждый компонент — это плагин. MCP-серверы, инструменты, скиллы, сессии, песочница, хранилище, циклы агента и даже сам UI — всё вынесено в плагины. Это позволяет менять поведение агента на уровне «под капотом»: заменять компоненты, переставлять части, менять сам способ действий агента. Для создания собственных плагинов есть отдельный Creator Mode: можно прямо в чате попросить «собери мне такой-то плагин для харнесса», и он будет создан и мгновенно переключён. Здесь же меняются настройки агентского цикла, системный промпт и провайдер веб-поиска (OpenAI, DeepSeek и другие). При этом есть и предостережение: вокруг уже появляются чужие open-source плагины, и неизвестно, что внутри, — к ним стоит относиться с той же осторожностью, что и к плагинам Claude Code или Codex.
Четыре режима работы
Харнесс работает в нескольких режимах. Standard — универсальный: больше времени на размышления, редактирование и чтение файлов, показ файлов, веб-поиск, публикация. PTC (plan-task-code) — раскладывает задачу на цепочки и исполняет их параллельно, мультичейном; ощущается почти как динамика Claude Code. Minimal — лёгкий кодинг-агент с системным промптом: потребляет заметно меньше контекста и исполняет задачи быстрее, но при старте нового чата не делает сокращение контекста, поэтому история не ужимается и остаётся видимой — в отличие от поведения Claude Code или Codex. Плюс есть отдельный режим для кастомных агентов. Отдельно ценно то, что харнесс без каких-либо настроек подхватывает скиллы и контекст из Claude Code — для миграции ничего менять не пришлось.
Скорость: главный козырь
Самый заметный результат тестов — радикальная разница в скорости. В side-by-side сравнении на одной и той же модели DeepSeek Harness обработал транскрипт и собрал саммари примерно за 50 секунд, пока Claude Code всё ещё искал исходный транскрипт. На более сложной задаче — креативный бриф для клиента с использованием нескольких систем — DeepSeek Harness управился примерно за 3 минуты, а Claude Code потребовалось около 17 минут. Харнесс показывает промежуточные шаги с гранулярностью до отдельных команд и сам продолжает двигаться к цели. Поскольку в сравнении использовалась одна и та же модель, разница объясняется именно эффективностью харнесса.
Баги и слабые места
Несмотря на скорость, харнесс ощущается как превью для разработчиков. В тестах встречались баги: один раз агент заблокировал мышь так, что курсор двигался только в маленьком квадрате; в длинных сессиях случались проблемы с компрессией контекста и контекстные регрессии; иногда агент просто переставал работать. Вторая заметная слабость — дизайн. Собранный на DeepSeek V4 Flash сайт с бренд-гайдлайнами и ассетами получился со «стандартным» ощущением — не уровня Claude Code или Codex, потому что у тех есть верификация через скриншоты: посмотреть на результат, отреагировать, итерировать. DeepSeek-модели так не умеют, и при работе с ними нужно осознавать сильные и слабые стороны моделей внутри харнесса.
Аналитика контента: другой стиль выводов
Показательный кейс — генерация отчёта по перформансу тренировочных видео (всего 467 роликов). DeepSeek Harness выдал цветовое кодирование по просмотрам и вовлечённости, лучших и худших видео, разбивку по категориям, графики месячных и недельных трендов, тег-анализ, заметки и источники — компактно, наглядно, без лишней воды. Claude Code на том же исследовательском скилле (Storm research skill) выдал текст примерно на 5000 слов — глубже и научнее, но гораздо многословнее и осторожнее в формулировках. DeepSeek делал акцент на key takeaways, связях и практических выводах, но иногда проявлял излишнюю уверенность в том, что фактами не подтверждено. По итогам больше доверия вызывает вывод Claude Code — его результат скорее захочется отдать клиенту или команде, хотя визуально отчёт DeepSeek был заметно лучше.
Заменяет ли Claude Code
Нет. Для глубокой работы — большие проекты, Opus в подписке Claude — харнесс Claude Code всё ещё впереди. Но бесплатный открытый харнесс DeepSeek с дешёвыми моделями — реальная альтернатива для тех, кому нужна скорость, дешёвый инференс и полная кастомизация. Важный нюанс: скиллы, написанные для Claude Code, при переносе в DeepSeek Harness интерпретируются иначе, — чтобы получить максимум, скиллы стоит собирать специально под этот харнесс. Итоговый совет — протестировать харнесс на своих реальных задачах и рабочих процессах и посмотреть, подходит ли он лично вам.
📜 Transcript
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My playbook for growing a $1M AI agency: https://app.aiautomationsociety.ai/opaa-ads-optin My FREE resources: https://www.skool.com/ai-automation-society/about?el=deepseek-harness-tested&hcategory=youtube-videos&utm_campaign=free-group My Tools💻 FREE MONTH voice to text: https://get.glaido.com/nate Code NATEHERK for 10% off VPS (annual plan): https://www.hostinger.com/vps/claude-code-hosting I spent a week testing Deepseek Harness to see how it compares with Claude Code in speed, output quality, cost, reliability, and customization. In this video, I walk through the interface, test both harnesses with the same model, and explain where Deepseek is already impressive and where it still feels like a developer preview. Sponsorship Inquiries: 📧 nate@smoothmedia.co Connect with me: https://www.linkedin.com/in/nateherkelman/ https://x.com/nateherk https://www.instagram.com/nateherk/ TIMESTAMPS 0:00 One Week With Deepseek Harness 0:18 What Is Deepseek Harness? 2:29 Setup, Models & Modes 5:52 Cost & Model Limitations 7:28 Reliability & Bugs 8:23 Unmatched Customization 10:42 Does It Replace Claude Code? 11:33 Speed Test: Deepseek vs Claude 13:43 Quality Test: Same Model 17:38 Final Verdict