DeepSeek V4 Pro — AI Model Review & Pricing
DeepSeek V4 Pro is a Mixture-of-Experts model with 1.6 trillion total parameters and 1M-token context, ranked #12 on LMRank. Launched as a preview in April 2026, it excels at coding, math, and agentic tasks, offering MIT-licensed weights and significantly lower cost than closed-source frontier models.
Specifications
| Attribute | Value |
|---|---|
| Lab | DeepSeek |
| Tags | Intelligent Open Weight Coding Reasoning Agentic |
| Release Date | 2026-03 |
| Context Window | 1,048,576 tokens |
| Input Price / 1M | $0.44 |
| Output Price / 1M | $0.87 |
| Input Modalities | Text |
| Output Modalities | Text |
Strengths
- Top open-weight model on agentic benchmarks (GDPval-AA #1)
- 1M-token context with efficient hybrid attention
- 4-7x cheaper than Claude Opus or GPT-5 per token
- MIT license allows full commercial use and fine-tuning
- Strong STEM reasoning and competitive coding performance
Weaknesses
- Text-only; no multimodal support
- High verbosity (180M eval tokens vs 100M average)
- Trails GPT-5 and Gemini-3.1-Pro on knowledge recall
- Self-hosting requires 865GB model and multi-GPU cluster
Best For
- Cost-sensitive production deployments
- Agentic workflows and tool-use pipelines
- Long-context reasoning over millions of tokens
- Math, coding, and STEM problem-solving
See what DeepSeek V4 Pro built
Interactive pages generated from the same creative briefs given to every model.
In Depth: DeepSeek V4 Pro
Benchmark Performance
With an LMRank score of 9.0/10 and #12 overall, DeepSeek V4 Pro leads all open-weight models on agentic tasks, scoring 1554 on GDPval-AA outpacing every other publicly weighted model in autonomous workflow execution.
DeepSeek V4 Pro delivers 90.1 EM on MMLU (5-shot) and 90.8 on MMLU-Redux, with 83.1 on AGIEval (0-shot). Independent evaluation by Artificial Analysis gives it an Intelligence Index of 52 (Max effort), ranking #3 among open-weight models. Unverified community reports claim 80.6% on SWE-bench Verified (Max) and 90.1% on GPQA Diamond, suggesting strong coding and reasoning capability.
Pricing & Value
DeepSeek V4 Pro costs $0.44 per million input tokens and $0.87 per million output tokens via OpenRouter roughly 4-7x less than equivalent closed-source frontier models.
At $0.435 input / $0.87 output per million tokens, DeepSeek V4 Pro delivers frontier-level reasoning for a fraction of the cost. Compared to Claude Opus 4.6 (~$15 input) or GPT-5 (~$10 input), teams can run 10-30x more tokens for the same budget. The direct DeepSeek API pricing is $1.74 input / $3.48 output. With MIT-licensed weights, self-hosting avoids per-token charges entirely on suitable hardware.
Who Should Use This
DeepSeek V4 Pro is built for cost-conscious teams who need near-frontier intelligence, agentic capabilities, and long-context reasoning without vendor lock-in.
- Startups: High performance at 4-7x lower cost than OpenAI/Anthropic, ideal for scaling
- Agent developers: Best open-weight model for autonomous tool-use workflows; tradeoff is text-only
- Researchers: MIT license enables full fine-tuning and redistribution; requires heavy compute
- Not ideal for multimodal projects: Text-only; wait for future vision support
Release & Version History
Released April 24, 2026 as a preview, DeepSeek V4 Pro succeeds V3.2 and integrates reasoning from DeepSeek-R1, representing DeepSeek's most capable open-weight model to date.
DeepSeek V4 Pro arrives nearly 16 months after V3.2 (December 2025), with a complete architectural overhaul including Compressed Sparse Attention and Manifold-Constrained Hyper-Connections. It is part of a two-model V4 Preview family alongside V4 Flash (284B total). The model inherits reasoning capabilities from DeepSeek-R1 via built-in thinking modes controlled by the reasoning_effort parameter. No successor has been announced as of June 2026.