Титульная карточка с надписью «СРАВНЕНИЕ МОДЕЛЕЙ — Step 5 Preview против DeepSeek V4.1 Pro», подзаголовком «У одной из этих двух моделей нет эндпоинта» и нижним колонтитулом, в котором отмечается, что показатели Step 5 Preview приведены по данным StepFun, а показатели DeepSeek V4 Pro — по прайс-листу DeepSeek.
Guides & Insights

Step 5 Preview против DeepSeek V4.1 Pro: один из них — не продукт

Автор

Elias Hawthorne

Дата публикации

Новые модели · 20Все модели →
Бенчмарки: Artificial Analysis · обновляется ежедневно
Назад ко всем статьям

You cannot call D​eepSeek V4.1 Pro. Not on a slow day, not at a higher price, not with a waitlist — there is no endpoint, no model card and no checkpoint anywhere, and there has not been since D​eepSeek named it. S​tep 5 Preview, by contrast, was released by StepFun on September 20, 2026, has been downloadable in three precisions since the morning of release, and has a published rate card, a million-token context window and one independent benchmark score. A comparison table between these two would be a comparison between a model and a name, so this piece is not that. It is the honest version: which of the two you can build on today, what the D​eepSeek tier was supposed to be, and what to actually route in its place while it does not exist.

Причина, по которой это сравнение вообще ищут, в том, что на бумаге они занимают одну и ту же нишу. Оба позиционируются как флагманские системы mixture-of-experts для сложной агентной работы и рассуждений, оба заявляют контекст в миллион токенов, и оба входят в семейства, где реально вышел именно младший брат. Разница в том, что каждый вендор сделал после того, как назвал свой флагман: StepFun опубликовал веса, рецепт сервинга и цену. DeepSeek опубликовал одно предложение, а затем отозвал его.

Что D​eepSeek на самом деле сказал, и что он сделал после этого

The single public appearance of the D​eepSeek V4.1 Pro name is in the September 10, 2026 release note for DeepSeek V4.1 Flash — the 552-billion-parameter multimodal model that is the V4.1 line's smallest member. In that note D​eepSeek wrote that from 04:00 UTC on September 14 all requests to deepseek-v4-pro/ would route to V4.1 Flash and be billed at Flash rates, and that this would continue "until V4.1-Pro launches." Developers running production traffic on the pinned Pro name objected to being silently moved onto a different model, and the plan was withdrawn. Nothing has been published about the Pro tier since.

So the correct reading of "D​eepSeek V4.1 Pro" today is: an announced intent, contingent on a launch date that has not been given, in a family where the Pro predecessor is a live, callable, separately-priced model. That predecessor is what the name is standing in for, and for anyone choosing an opponent this week it is the only real one on the D​eepSeek side of the fence.

Сравнение, которое вы действительно можете запустить

Here is S​tep 5 Preview against the callable D​eepSeek flagship, with every row sourced. The D​eepSeek column is DeepSeek V4 Pro, not V4.1 Pro, and that substitution is the whole point of the table.

• Price per million tokens — S​tep 5 Preview $1.00 input, $0.10 cache-hit input, $2.70 output, flat around the clock vs DeepSeek V4 Pro $0.66 input, $0.022 cache-hit input, $1.98 output off-peak, doubling to $1.32 / $0.044 / $3.96 during D​eepSeek's peak hours

• Context window — S​tep 5 Preview 1M tokens vs DeepSeek V4 Pro 1,048,576 tokens

• Maximum output — S​tep 5 Preview 64k tokens in StepFun's documentation, though the model card's own specification table says "up to 1M" vs DeepSeek V4 Pro 384,000 tokens

• Architecture — S​tep 5 Preview sparse MoE, 600B total and 27B active, 352 experts with 8 selected per token across 88 of its 92 layers vs DeepSeek V4 Pro MoE, 1.6 trillion total and 49 billion active

• Input modality — S​tep 5 Preview text, images and video vs DeepSeek V4 Pro text only

• Independent score — S​tep 5 Preview 44 on the Artificial Analysis Intelligence Index, at rank 41 of 219 when that page was captured vs DeepSeek V4 Pro no public equivalent row on the same board

• Median time to first token on OrcaRouter — S​tep 5 Preview not routed, so no row vs DeepSeek V4 Pro 1.89 seconds

• Weights — S​tep 5 Preview FP8, BF16 and NVFP4 repositories, all under StepFun's own account, ungated vs DeepSeek V4 Pro open weights on Hugging Face

An independent evaluation page for Step 5 Preview, showing the launch marker "Released September 2026", a proprietary-licence label and the heading "Step 5 Preview Intelligence, Performance & Price Analysis".

Строка о потолке вывода заслуживает отдельного предложения, потому что это единственное место, где собственные материалы двух вендоров противоречат сами себе. В документации StepFun указан максимальный объём вывода 64k. В карточке модели StepFun в том же релизе в таблице характеристик написано «до 1M токенов». Оба документа принадлежат StepFun, оба актуальны, и эта разница — разница между ограничением из документации и архитектурным ограничением. Пока кто-нибудь не опубликует завершение на 200k токенов, считайте 64k тем числом, которое вы получите от хостингового API.

A two-column scoreboard titled "Step 5 Preview vs DeepSeek V4 Pro", with a footer noting that DeepSeek V4.1 Pro has no published data and that the right-hand column is DeepSeek V4 Pro at off-peak rates. Step 5 Preview: $1.00 / $2.70, cached input $0.10, 1M-token context, 64k maximum output, text plus image plus video input, index score 44. DeepSeek V4 Pro: $0.66 / $1.98, cached input $0.022, 1,048,576-token context, 384,000-token maximum output, text only, no published index row.

Почему разница в цене меньше, чем кажется

DeepSeek V4 Pro is the cheaper model on both ends of the rate card — 34% less on input, 27% less on output — and its cache-hit rate, two cents per million tokens, is an order of magnitude below S​tep 5 Preview's ten. That is a real and large advantage for workloads with a stable prefix: a retrieval pipeline that re-sends the same 300,000-token document set on every call pays $6.60 per million calls on D​eepSeek and $30.00 on StepFun, and nothing else in the comparison closes that gap. The comparison assumes D​eepSeek's off-peak rate, which is the one its documentation leads with; that rate applies outside two windows, 01:00–04:00 and 06:00–10:00 UTC Monday to Friday, and inside them every line on the D​eepSeek card doubles. A workload that runs on United States business hours spends a meaningful share of its week in the peak window, where DeepSeek V4 Pro costs $1.32 input, $0.044 cached and $3.96 output — still cheaper than StepFun on input and now more expensive on cache reads, against a S​tep 5 Preview rate that does not move with the clock.

What closes some of it is verbosity. On the same evaluation suite, S​tep 5 Preview generated 160 million output tokens against a suite median of 85 million — the evaluator's own note calls it "very verbose" — and it does not publish an equivalent token count for DeepSeek V4 Pro, so the honest position is that the cache advantage is measurable and the output-token penalty is measurable on one side only. If your prompts are long, stable and cache-heavy, DeepSeek V4 Pro is the cheaper purchase and the gap is wide. If they are short and highly variable, most of the input is billed as cache misses and the two rate cards land within a third of each other.

The modality split is the other thing price does not capture. DeepSeek V4 Pro is text-only. S​tep 5 Preview reads images and video, and that is not a feature you can price against a text-only model — it is a workflow you either have or you do not. Screenshot triage, chart extraction and video summarisation are out of scope on the D​eepSeek flagship and in scope here, and no discount on input tokens buys them back.

Маршрутизация в обход несуществующей модели

Практический вопрос, который поднимает это сопоставление, заключается в том, что делать, когда у модели, которую вы планировали использовать, есть имя, но нет эндпоинта. Перенацелить константу в клиенте — это простая часть. Сложнее то, что привязка к уровню, который так и не был выпущен, заставляет вас самостоятельно принимать то же решение о замене в самый неподходящий момент, и именно здесь слой маршрутизации оправдывает своё место.

DeepSeek V4 Pro is on OrcaRouter, and so is the model that replaced it in D​eepSeek's own lineup: the catalogue carries both deepseek/deepseek-v4-pro/ and deepseek/deepseek-v4.1-flash/, which means an A/B against the successor D​eepSeek itself recommends is a change to one string in the model parameter rather than a second contract, a second SDK and a second bill. Requests go to the same O​penAI-compatible endpoint either way, at 0% markup on the provider's list price — $0.66 and $1.98 per million for V4 Pro is exactly D​eepSeek's own rate, passed through untouched, so a vendor price change reaches you the day it happens rather than on the next billing cycle.

OrcaRouter's model page for DeepSeek V4 Pro, showing the catalogue path deepseek/deepseek-v4-pro, a 1M-token context, a 384K maximum output and the DeepSeek vendor label. This is OrcaRouter's own page.

That covers the D​eepSeek side of the question and not the StepFun side, because S​tep 5 Preview is not on OrcaRouter's live model list — it is not routed here, and the way to call it is StepFun's own API. What the router gives you in that arrangement is a fallback floor: one endpoint, one key and one bill that carries the models you can call today, against a vendor endpoint you are integrating for the one you cannot get anywhere else. Automatic failover matters more than usual on a model this new, because a primary provider going down at 3am should not mean a production path going down with it.

Для чего на самом деле предназначено каждое из них

DeepSeek V4 Pro — это выбор, когда нагрузка текстовая, префикс промпта стабилен, доля попаданий в кэш высока и важен потолок вывода в 384 000 токенов — для длинноконтекстной работы с документами и кодом, где большая часть входных данных каждый раз одна и та же и модель просят дополнить, а не переписать. Он также является выбором, когда для задачи не нужна картинка. При такой нагрузке 34%-ная скидка на вход и двухцентовая ставка кэша становятся решающими, а отсутствие преемника V4.1 Pro — аргумент в пользу зафиксированной, стабильной, уже выпущенной модели, а не против неё.

S​tep 5 Preview is the pick when the task is agentic and multimodal: a repository-scale coding session with screenshots in the loop, a research run over mixed documents and video, or a finance workflow that has to read the tables in a filing rather than the text around them. StepFun built this model for sustained tool use, published a serving recipe that handles its reasoning and tool-call formats properly, and put the weights out so that a data-residency requirement does not rule it out. It costs roughly half again what DeepSeek V4 Pro costs on input and a third more on output, and on a cache-heavy text workload that premium is hard to justify. On a workload with images in it there is no comparison to make, because one of the two models cannot see.

And D​eepSeek V4.1 Pro is not a pick at all. When it ships it will presumably be the largest model in the V4.1 family and will be priced above V4.1 Flash; D​eepSeek has said so implicitly by naming a Pro tier at all. Nothing about it is knowable today beyond the one sentence from September 10, and anyone publishing specs for it is publishing an inference. If you have capacity plans that assume it, the safest assumption available is that it arrives later than you hope and costs more than you budgeted.

Краткая версия

Two models get compared here and only one exists. S​tep 5 Preview was released on September 20, 2026, is callable on StepFun's platform at $1.00 and $2.70, reads text, images and video, and has an open-weights story that turned out to be true all along. D​eepSeek V4.1 Pro is a tier name in a release note that D​eepSeek has not followed with a model card, an endpoint or a date. For a text workload with a stable prefix, the model to compare S​tep 5 Preview against is DeepSeek V4 Pro, which is cheaper on every line, callable today, and available alongside the rest of the catalogue on one key. For anything with an image in it, there is no D​eepSeek comparison to run.

Чего цифры не могут вам сказать, так это того, не пошло ли что-то не так на практике: задокументированные инциденты с ИИ и сбои агентов, связанные с моделями этого класса, собраны в архиве инцидентов ИИ OrcaRouter, где каждая запись сопровождается собственными источниками, оценкой серьёзности, уровнем достоверности и отметкой о спорности.

Сравнение в этой статье1

Определено по этой статье · Бенчмарки: Artificial Analysis · обновляется ежедневно