The DeepSeek V4 model family (ID: deepseek/deepseek-v4), officially unveiled on April 24, 2026, marked a new stage in the development of open large language models. If GPT-5.5 takes the lead through flawless “intuition” and creativity, DeepSeek V4 dominates in raw performance, open weights, and phenomenal economic efficiency.
This is the release that cemented the “million-token context” as an industry standard and transitioned DeepSeek from the status of a bold startup to a mature systems integrator with products for every need.
🧩 Architecture: A Giant on a Diet
The entire DeepSeek V4 lineup is built on the next-generation MoE (Mixture of Experts) architecture. The key innovation is the introduction of a Hybrid Attention mechanism, which involves Compressed Sparse Attention (CSA) and Highly Compressed Attention (HCA).
What this means in practice:
- Reduced Computational Load: When processing a massive 1 million token context, the model requires only 27% of the computational resources (FLOPs) compared to its V3.2 predecessor.
- Memory Savings: KV Cache memory consumption for long contexts is reduced to 7–10%.
- Scale: A colossal knowledge base where only a small fraction of parameters are activated for each request.
🚀 Detailed Overview of the V4 Lineup
DeepSeek didn’t introduce just one model, but an entire ecosystem separated by tasks and power. Flexible reasoning modes are also available to developers: Non-think (fast response), Think High (advanced logic), and Think Max (maximum analysis level for complex coding).
DeepSeek-V4-Pro (Flagship)
The most powerful model for complex intellectual tasks, deep programming, and research agents. In think-max mode (Pro-Max), it scores 90.2 points on the HumanEval benchmark.
| Feature | Metric | Note |
|---|---|---|
| ID | deepseek/deepseek-v4-pro | Flagship solution |
| Parameters (Total/Active) | 1.6T / 49B | Largest open model |
| Context Window | 1,000,000 tokens | ~750,000 words |
| API Cost | $1.74 input / $3.48 output | Per 1 million tokens |
| License | MIT (Open weights) | Disk size ~865 GB (FP16) |
DeepSeek-V4-Flash (Economical Speed)
A separately trained lightweight model—the perfect balance between performance and cost. Optimized for mass serving, data extraction, and routing. It is over 99% cheaper than super-heavy commercial solutions from competitors.
| Feature | Metric | Note |
|---|---|---|
| Model ID | deepseek/deepseek-v4-flash | Fast and economical version |
| Parameters (Total/Active) | 284B / 13B | Lightweight architecture |
| Context Window | 1,000,000 tokens | The same giant context |
| API Cost | $0.14 input / $0.28 output | Per 1 million tokens |
| License | MIT (Open weights) | Disk size ~160 GB (FP16) |
Other Versions
- DeepSeek-V4 Lite — An ultra-light version that retains multimodality (capable of not only understanding but also generating images), unlike the strictly textual Flash.
- DeepSeek R2 — A specialized model for complex mathematical logic and theorem proving (release expected later).
- DeepSeek OCR-2 — A compact (3B parameters) specialized model for recognizing complex documents and blueprints.
⚔️ Comparison: DeepSeek V4 Pro vs OpenAI GPT-5.5
DeepSeek V4 was developed with a special focus on autonomous agents and coding. It perfectly fits into automation frameworks (e.g., OpenClaw).
| Parameter | DeepSeek V4 Pro | OpenAI GPT-5.5 |
|---|---|---|
| Availability | Open (MIT), Local launch | Closed (Cloud/API only) |
| API Cost | ~$1.74 / $3.48 | $5.00 / $30.00 (~3-8x more expensive) |
| Strengths | Code, Math, Algorithms | Creativity, Visuals, Empathy, General Intelligence |
| Context | 1M tokens (super-efficient) | 1M tokens |
💎 Summary: Why Does It Change the Game?
The main value of DeepSeek V4 is the democratization of AI. The model offers GPT-5.5 level intelligence (especially in writing code) but at a price and with a license that allow running massive automated systems, trading bots, or enterprise platforms without colossal token budgets or vendor lock-in to another company’s API. The model natively supports NVIDIA NIM and vLLM platforms, as well as Huawei Ascend 950 chips.
If GPT-5.5 is the “universal digital genius,” then DeepSeek V4 is the “tireless brilliant engineer” ready to work day and night virtually for free on your own servers.
❓ Frequently Asked Questions
How is DeepSeek V4 different from GPT-5.5?
DeepSeek V4 is an open-weights (MIT) model focused on coding, math, and logic, distributed locally or via an ultra-cheap API. GPT-5.5 is a proprietary closed model that excels in creative tasks and empathy but is significantly more expensive.
How much does the DeepSeek V4 API cost?
The cost depends on the version. The flagship V4-Pro costs $1.74 per million input and $3.48 per million output tokens. The lightweight V4-Flash costs only $0.14 / $0.28, respectively.
Can DeepSeek V4 be run locally?
Yes, all models in the family come with open weights under the MIT license. The Flash version weighs about 160 GB and can be run on powerful workstations (e.g., with two modern graphics cards); the flagship Pro (865 GB) will require server hardware.
What are reasoning modes in DeepSeek V4?
These are AI operational modes: Non-think (basic, fastest for simple requests), Think High (advanced reasoning), and Think Max (used in the flagship for multi-step code self-verification or complex algorithms, sacrificing speed for better results).
Is DeepSeek V4 good for writing code?
Absolutely. In the deep thinking mode (Pro-Max), the model scores 90.2 points on the HumanEval benchmark and performs at the level of cutting-edge closed systems, making it the ideal engine for AI agents.