Analysis Summary
DeepSeek V4 Pro is a high-capability model with strong measured reasoning, coding, and agentic performance. It supports tool use and function calling, offers a 1M-token context window, and records strong results for instruction following, long-context work, terminal tasks, and tool-based interaction. Its text-only modality is the main practical constraint.
For businesses, the combination is well suited to software engineering, codebase analysis, document-heavy research, and multi-step operational agents. Reliable tool interaction makes it a credible choice for workflows that need actions rather than chat alone. The roughly one-dollar input and two-dollar output pricing favors high-value tasks, where deeper reasoning offsets token cost, rather than indiscriminate bulk generation.
Assessed September 7, 2026
Editorial notes
DeepSeek V4 Pro combines strong reasoning, high coding capability, reliable tool interaction, and a 1M-token context window. It fits demanding engineering and document workflows, though its pricing is better suited to high-value tasks than bulk traffic.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
DeepSeek V4 Pro combines strong reasoning, high coding capability, reliable tool interaction, and a 1M-token context window. It fits demanding engineering and document workflows, though its pricing is better suited to high-value tasks than bulk traffic.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
42.1 Intelligence Index·68.8 Coding Index·42.5 Agentic Index
How DeepSeek: DeepSeek V4 Pro compares
DeepSeek: DeepSeek V4 Pro ranks #38 of 435 AI models we track for overall intelligence, #37 of 208 for coding, #37 of 190 for agentic tasks. Its 1M-token context window is larger than 94% of the models we list. At $0.96 per million input tokens it is cheaper than 28% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on business fit. The pulled-in intelligence corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.96 | $0.000955 |
| Output | $1.91 | $0.001911 |
What would DeepSeek: DeepSeek V4 Pro cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 756 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save DeepSeek: DeepSeek V4 Pro for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout DeepSeek: DeepSeek V4 Pro
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,..
Explore Related Models
Frequently asked questions about DeepSeek: DeepSeek V4 Pro
How much does DeepSeek: DeepSeek V4 Pro cost?
DeepSeek: DeepSeek V4 Pro costs $0.96 per million input tokens and $1.91 per million output tokens.
What is the context window of DeepSeek: DeepSeek V4 Pro?
DeepSeek: DeepSeek V4 Pro has a context window of 1,048,576 tokens (1M).
Is DeepSeek: DeepSeek V4 Pro good for coding?
On our coding benchmark index, DeepSeek: DeepSeek V4 Pro ranks #37 of 208 models, placing it in the top quartile of the field for code generation and debugging.
What can DeepSeek: DeepSeek V4 Pro do?
DeepSeek: DeepSeek V4 Pro supports tool use and function calling.
Who created DeepSeek: DeepSeek V4 Pro?
DeepSeek: DeepSeek V4 Pro is developed by DeepSeek and was released on April 24, 2026.
Data sourced from the OpenRouter API, Artificial Analysis, the Hugging Face Open LLM Leaderboard and our own internal testing. Scores are editorially curated by our team.
Last updated: September 7, 2026 8:38 pm