
Step 5 Preview so với DeepSeek V4.1 Pro: Một trong những thứ này không phải là sản phẩm
- OrcaMỚIOrca: OrcaCyber Zero 1.52026-10-10$3.00 / $7.50 trên 1 triệu token · 72 tok/s
- openaiOpenAI: GPT-6.1 Sol2026-09-2952Trí tuệ
- anthropicAnthropic: Claude Sonnet 5.52026-09-2856Trí tuệ
- typesafeTypeSafe: Jev 1.132026-09-24$0.04 / $0.00 trên 1 triệu token · 737 tok/s
- OpenAIOpenAI: GPT-6 Luna2026-09-2238Trí tuệ
- OpenAIOpenAI: GPT-6 Sol2026-09-2248Trí tuệ
- AnthropicAnthropic: Claude Opus 5.52026-09-2258Trí tuệ
- xAIGrok 4.72026-09-2146Trí tuệ
- OrcaOrca: OrcaCyber Zero 1.02026-09-17$3.00 / $7.50 trên 1 triệu token · 35 tok/s
- OrcaOrca: OrcaVerify Text 1.02026-09-16$2.00 / $0.00 trên 1 triệu token · 821 tok/s
- DeepSeekDeepSeek: DeepSeek V4.1 Flash2026-09-1040Trí tuệ
- OpenAIOpenAI: GPT-6 Astra2026-09-0453Trí tuệ77Lập trình
- GoogleGoogle: Gemini 3.8 Flash2026-09-0241Trí tuệ76Lập trình
- AlibabaQwen: Qwen3.8 Max (0902)2026-09-0245Trí tuệ76Lập trình
- AnthropicAnthropic: Claude Fable 5.12026-09-0153Trí tuệ82Lập trình
- TencentTencent: Hy4 preview2026-08-28$0.83 / $2.50 trên 1 triệu token · 52 tok/s
- AlibabaQwen: Qwen3.8 Flash2026-08-26$0.15 / $0.47 trên 1 triệu token · 108 tok/s
- z-aiZ.ai: GLM 5.3 Flash2026-08-2642Trí tuệ72Lập trình
- DeepSeekDeepSeek: DeepSeek V4 Flash Vision (Exp)2026-08-21$0.22 / $0.66 trên 1 triệu token · 184 tok/s
- z-aiZ.ai: GLM 5.32026-08-1845Trí tuệ75Lập trình
You cannot call DeepSeek 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 DeepSeek named it. Step 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 DeepSeek 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. DeepSeek published a sentence, then withdrew it.
What DeepSeek actually said, and what it did next
The single public appearance of the DeepSeek 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 DeepSeek 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 "DeepSeek 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 DeepSeek side of the fence.
Bài so sánh mà bạn thực sự có thể chạy
Here is Step 5 Preview against the callable DeepSeek flagship, with every row sourced. The DeepSeek column is DeepSeek V4 Pro, not V4.1 Pro, and that substitution is the whole point of the table.
• Price per million tokens — Step 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 DeepSeek's peak hours
• Context window — Step 5 Preview 1M tokens vs DeepSeek V4 Pro 1,048,576 tokens
• Maximum output — Step 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 — Step 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 — Step 5 Preview text, images and video vs DeepSeek V4 Pro text only
• Independent score — Step 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 — Step 5 Preview not routed, so no row vs DeepSeek V4 Pro 1.89 seconds
• Weights — Step 5 Preview FP8, BF16 and NVFP4 repositories, all under StepFun's own account, ungated vs DeepSeek V4 Pro open weights on Hugging Face

Dòng về mức trần đầu ra xứng đáng có một câu riêng, vì đây là nơi duy nhất tài liệu của chính hai nhà cung cấp tự mâu thuẫn với chính mình. Tài liệu của StepFun ghi đầu ra tối đa là 64k. Thẻ mô hình của StepFun, trong cùng bản phát hành, lại in "Tối đa 1M token" trong bảng thông số kỹ thuật. Cả hai đều là tài liệu của StepFun, cả hai đều hiện hành, và sự khác biệt là sự khác biệt giữa một giới hạn theo tài liệu và một giới hạn mang tính kiến trúc. Cho đến khi có ai đó đăng một completion dài 200k token, hãy coi 64k là con số bạn sẽ nhận được từ API được host.

Vì sao chênh lệch giá lại nhỏ hơn vẻ ngoài của nó
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 Step 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 DeepSeek and $30.00 on StepFun, and nothing else in the comparison closes that gap. The comparison assumes DeepSeek'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 DeepSeek 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 Step 5 Preview rate that does not move with the clock.
What closes some of it is verbosity. On the same evaluation suite, Step 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. Step 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 DeepSeek flagship and in scope here, and no discount on input tokens buys them back.
Định tuyến quanh một mô hình không tồn tại
Câu hỏi thực tế mà sự đối chiếu này đặt ra là phải làm gì khi mô hình bạn định dùng có tên nhưng không có endpoint. Việc thay đổi đích của hằng số trong client của bạn là phần dễ. Phần khó hơn là việc ghim vào một tầng chưa từng được phát hành khiến bạn phải tự mình đưa ra quyết định thay thế tương tự, vào đúng thời điểm tồi tệ nhất, và đây chính là lúc lớp định tuyến chứng minh được giá trị của nó.
DeepSeek V4 Pro is on OrcaRouter, and so is the model that replaced it in DeepSeek'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 DeepSeek 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 OpenAI-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 DeepSeek'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 DeepSeek side of the question and not the StepFun side, because Step 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.
Công dụng thực sự của từng thứ trong số này là gì
DeepSeek V4 Pro là lựa chọn khi khối lượng công việc là văn bản, tiền tố prompt ổn định, tỷ lệ cache hit cao và giới hạn đầu ra 384.000 token quan trọng — công việc tài liệu và mã nguồn theo ngữ cảnh dài, nơi phần lớn đầu vào giống hệt nhau mỗi lần và mô hình được yêu cầu mở rộng thay vì viết lại. Nó cũng là lựa chọn khi không có gì trong tác vụ cần hình ảnh. Với khối lượng công việc đó, mức chiết khấu 34% cho đầu vào và mức giá cache hai xu là yếu tố quyết định, và việc không có phiên bản kế nhiệm V4.1 Pro là một lập luận ủng hộ một mô hình đã được ghim, ổn định, đã phát hành, chứ không phải chống lại nó.
Step 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 DeepSeek 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; DeepSeek 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.
Phiên bản ngắn
Two models get compared here and only one exists. Step 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. DeepSeek V4.1 Pro is a tier name in a release note that DeepSeek has not followed with a model card, an endpoint or a date. For a text workload with a stable prefix, the model to compare Step 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 DeepSeek comparison to run.
Điều mà những con số không thể cho bạn biết là liệu có bất kỳ phần nào trong đó đã gặp trục trặc trong thực tế hay không: các sự cố AI và lỗi agent được ghi nhận liên quan đến các mô hình thuộc lớp này được tập hợp trong OrcaRouter AI Incident Archive, nơi mỗi mục đều có nguồn riêng, mức độ nghiêm trọng, xếp hạng độ tin cậy và cờ tranh chấp.
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