Step 5 Preview vs DeepSeek V4.1 Pro: 이 중 하나는 제품이 아니다

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.

The reason this matchup gets searched at all is that the two occupy the same slot on paper. Both are advertised as flagship-class mixture-of-experts systems for hard agentic and reasoning work, both quote a million-token context, and both sit in families where the smaller sibling is the one that actually shipped. The difference is what each vendor did after naming its flagship: StepFun published weights, a serving recipe and a price. D​eepSeek published a sentence, then withdrew it.

What D​eepSeek actually said, and what it did next

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production traffic on the pinned Pro name objected to being silently moved onto a different model, and the plan was withdrawn.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.

실제로 실행할 수 있는 비교

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

출력 상한 행은 별도의 문장으로 다룰 만합니다. 그곳이 두 벤더의 자체 자료가 스스로와 어긋나는 유일한 지점이기 때문입니다. StepFun의 문서에는 최대 출력 64k라고 되어 있습니다. 같은 릴리스의 StepFun 모델 카드에는 사양 표에 "최대 1M 토큰"이라고 적혀 있습니다. 둘 다 StepFun 문서이고, 둘 다 최신이며, 그 차이는 문서상 한계와 아키텍처상 한계 사이의 차이입니다. 누군가 200k 토큰 완성 결과를 올리기 전까지는 64k를 호스팅 API에서 얻게 될 수치로 취급하세요.

가격 차이가 보이는 것보다 작은 이유

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.

존재하지 않는 모델을 우회하는 라우팅

이 맞대결이 제기하는 실질적인 질문은, 사용하려던 모델에 이름은 있지만 엔드포인트가 없을 때 무엇을 해야 하느냐이다. 클라이언트에서 상수를 재지정하는 것은 쉬운 부분이다. 더 어려운 부분은, 한 번도 출시된 적 없는 티어에 고정해 두면 가장 최악의 시점에 혼자서 똑같은 대체 결정을 내려야 한다는 점이며, 바로 이 지점에서 라우팅 계층이 제 역할을 한다.

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.

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.

이들 각각이 진정으로 무엇을 위한 것인지

DeepSeek V4 Pro는 워크로드가 텍스트이고, 프롬프트 접두사가 안정적이며, 캐시 적중률이 높고, 384,000 토큰의 출력 상한이 중요할 때 선택입니다 — 입력 대부분이 매번 동일하고 모델이 다시 쓰기보다 확장하도록 요구받는 장문 맥락 문서 및 코드 작업에서요. 또한 작업에 그림이 전혀 필요 없을 때도 선택입니다. 그런 워크로드에서는 34% 입력 할인과 2센트 캐시 요율이 결정적이며, V4.1 Pro 후속 모델의 부재는 고정된, 안정적이며, 이미 출시된 모델을 반대하는 논거가 아니라 지지하는 논거입니다.

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.

짧은 버전

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.

숫자만으로는 이런 것들 중 어느 하나라도 현장에서 잘못된 적이 있는지 알 수 없습니다. 이 등급의 모델과 관련해 문서화된 AI 사고와 에이전트 실패 사례는 the OrcaRouter AI Incident Archive에 수집되어 있으며, 각 항목에는 자체 출처, 심각도, 신뢰도 등급, 이의 제기 여부 표시가 함께 제공됩니다.