大模型网摘DeepSeek-V4-Pro-0813 Explained: Open Weights, Million-Token Context and Dual-Mode Snapshot
While the V4.1-Flash line hogs the headlines, DeepSeek's flagship track keeps moving: DeepSeek-V4-Pro-0813 (the August 13 snapshot) is currently the company's flagship-tier model, available both via the official API and as open weights. Drawing on public data from model aggregators and third-party platforms, here is a snapshot-style breakdown of its specs, positioning and best-fit scenarios.
Specs at a glance
Per models.dev and similar aggregators: context window of 1,048,576 tokens (~1M), output cap of 384,000 tokens (393,216 on the official endpoint); thinking and non-thinking dual modes switchable per request; and capability tags covering tool calling, reasoning and temperature control. On weights, the snapshot ships open, so enterprises can self-host — consistent with the philosophy behind DeepInfer, DeepSeek's open-sourced inference framework.
Positioning: Flash for volume, Pro for the flagship
Within the lineup, V4.1-Flash handles high-volume, high-frequency workloads (low price, fast responses, native vision), while V4-Pro-0813 holds the flagship slot: longer context and deeper reasoning for long-document analysis, complex codebase comprehension and multi-step agent tasks. The two are layered, not interchangeable — our October model roundup maps the full division of labor; this piece fills in the Pro snapshot's details.
Pricing and access: official is cheap, third parties charge for convenience
The official API costs $0.66 input / $1.98 output per million tokens (as of press time). On the third-party side, 52 providers carry the model across a wide price band: budget aggregators dip to around $0.69 input, while mainstream clouds (Cloudflare, Together, etc.) cluster around $1.32/$3.96. The premium buys convenience, regional latency and enterprise billing. Do the math before choosing: heavy workloads belong on the official API or budget channels, while small experiments can run wherever is handy.
When Pro is worth it
Three task classes play to V4-Pro-0813's strengths: very long documents — the million-token window ingests book-length material in one pass; complex reasoning and planning — thinking mode holds up better on multi-step math and code architecture; self-hosted enterprise deployments — open weights plus DeepInfer keep data in-house. For lightweight, high-frequency use, the Flash line remains the better value; see our earlier agentic coding cost comparison.
Bottom line
V4-Pro-0813 matters because DeepSeek fields its flagship capability in two markets at once — API and open weights — without a flagship-sized price premium. For developers it is a self-hostable high-spec engine; for the industry, the open-weights-plus-million-token combo keeps pushing the cost curve of long-context applications downward. We will follow new snapshots in the Models channel as they land.