What is DeepSeek and how it can help you be more productive
DeepSeek isn’t just “the Chinese ChatGPT” anymore. What started in January 2025 as a surprise open-weight release that shook global markets has become a permanent fixture of the AI landscape: a free chat app, an open model family you can download and run yourself, and API pricing that keeps dragging the entire industry down. In April 2026 DeepSeek shipped its V4 generation – V4 Pro and V4 Flash, both with a 1 million-token context window – and by August 2026 V4 Pro had exited preview with frontier-adjacent coding and reasoning scores at a fraction of Western rivals’ prices.
In this guide we explain what DeepSeek is in 2026, how the V4 Pro and V4 Flash models work, why open weights and MIT licensing matter, why R2 still hasn’t shipped, what the app and API cost, and how to use DeepSeek well.
What is DeepSeek?
DeepSeek is a Chinese AI research lab – and the assistant built around its models – founded in 2023 by Liang Wenfeng, a quant fund manager who runs the hedge fund High-Flyer. The lab started as High-Flyer’s research arm before spinning out on its own. The name isn’t an acronym; it translates roughly to “deep exploration,” the company’s chosen nod to the idea of searching hard for better answers. DeepSeek caught the world’s attention in January 2025 when its R1 reasoning model matched Western frontier models at a fraction of the cost – triggering what markets dubbed a “Sputnik moment” for open-weight AI.
Today DeepSeek is a complete package, not just a research lab. Depending on where you use it, it can:
- Answer questions & explain concepts
- Write, rewrite, summarize & translate
- Search the web with citations
- Reason step by step with Think modes
- Process 1M-token documents
- Write, debug & review code
- Analyze spreadsheets & data
- Run locally on your own hardware
- Serve cheap API calls at scale
DeepSeek V4: Pro and Flash
DeepSeek’s current generation is V4, released as a preview on April 24, 2026 – exactly a year after the V3 era that rattled Silicon Valley. V4 ships in two sizes, both with a 1 million-token context window, both open-weight under the MIT license. V4 Pro left preview on August 13, 2026; V4 Flash remains the fast, low-cost workhorse.
Two notes on the wider lineup. First, the R series: R1 made DeepSeek famous in January 2025, and its successor R2 has been rumored, teased, and expected ever since – but as of August 2026 it still hasn’t shipped. DeepSeek appears to be holding it back rather than release something below its own bar, so R1-0528 remains the standalone reasoning option while V4 integrates reasoning directly into every response. Second, the older V3 family (V3, V3.1, V3.2) is still widely deployed and fine-tuned in the open-weight community, even though new development has moved to V4.
How does DeepSeek work?
DeepSeek models are Mixture-of-Experts transformers: only a fraction of the total parameters are active for any given token, which is how a 1.6-trillion-parameter model can answer so cheaply. V4 adds a hybrid attention design – compressed sparse attention combined with a second attention path – that DeepSeek says cuts compute to about 27% of V3.2’s and shrinks the KV cache to a tenth at 1M-token context lengths.
V4 also folded reasoning into the main models instead of keeping it in a separate R-series line. You pick a thinking level per request:
- 1
Non-thinking mode
The fastest, cheapest mode for routine questions, summarization, and drafting – answers in a single pass.
- 2
Think mode
The default reasoning level for hard questions – the model works through the problem step by step before answering, like the old R1 line.
- 3
Think Max
The deepest reasoning budget for the hardest problems – note that it needs a 384K-token minimum context window, so it consumes part of your context budget.
- 4
Tools on top
Like its rivals, V4 combines the model with tools: live web search, file uploads, and the API surface that powers agentic coding workflows.
What can you do with DeepSeek?
Why open weights matter
The single most important thing to understand about DeepSeek is the license. Every DeepSeek model – V3, R1, and the V4 family – ships under the permissive MIT license with weights published on Hugging Face. Anyone can download the full model, fine-tune it, integrate it, resell it, or run it on their own hardware with no payment and no approval. That is very different from “open” in the marketing sense: GPT-5.5, Claude, and Gemini are closed; Llama and Qwen are open-weight but with usage restrictions; DeepSeek is about as open as frontier models get.
DeepSeek timeline: 2023–2026
High-Flyer’s research arm becomes DeepSeek, a full AI lab; early DeepSeek Coder and Chat models arrive later that year.
DeepSeek V3 launches: a 671-billion-parameter MoE model trained at a fraction of Western costs, with open weights that immediately feed the open-source community.
R1, a step-by-step reasoning model, becomes a global phenomenon: the free app tops app-store charts, and markets briefly wipe roughly a trillion dollars off US tech stocks – the “Sputnik moment.”
V3.1 and then V3.2 refine the general model; R1-0528 updates the reasoning line. R2 is rumored but never arrives.
V4 Preview ships quietly – no press release, just model cards and API docs. V4 Pro (1.6T/49B active) and V4 Flash (284B/13B active), both with 1M context, MIT weights, and a 75% introductory price cut.
DeepSeek makes the 75% discount permanent; the old deepseek-chat and deepseek-reasoner API ids are retired in July after a long deprecation window.
V4 Pro exits preview (Aug 13) and API pricing moves to peak/off-peak windows from Aug 16. R2 still hasn’t shipped – the most-requested model in AI that doesn’t exist yet.
How to use DeepSeek well
The prompt pattern that works
Context, task, constraints – with a 1M window, give it everything and let it decide what matters. For sensitive or regulated work, self-host the weights and keep the data in-house.
How large is the context window?
Both V4 models support a standard 1 million-token context window – roughly 750,000 words – with up to 384,000 tokens of output. That is enough to hold an entire codebase or a book-length document in a single prompt, and the hybrid attention design is what keeps that long a window affordable to serve.
Practical rule of thumb: a token is roughly 0.75 English words, and about 1.5 tokens per word once you factor in punctuation and spacing. Two caveats at the long end: attention is not uniformly strong across a 1M window – every frontier model shows some “lost in the middle” degradation – and Think Max mode requires a 384K-token minimum context, which eats into the budget your actual query would otherwise use.
What does DeepSeek cost?
| Plan | Price | What you get | Limits |
|---|---|---|---|
| DeepSeek app | $0 | Free chat with V4 Pro / V4 Flash, web search, file uploads | No consumer paid plan exists as of August 2026 – the app is free |
| API – V4 Pro | $0.435 in / $0.87 out per 1M | Flagship reasoning, 1M context, Think modes | $0.003625 cached input; peak/off-peak pricing from Aug 16, 2026 |
| API – V4 Flash | $0.14 in / $0.28 out per 1M | Fast everyday tasks and high-volume workloads | $0.0028 cached input |
| Self-hosted | Free (MIT) | Full model weights, unlimited use, data stays in-house | Hardware is on you: quantized Flash fits high-end consumer gear; Pro needs a multi-GPU server |
For context: V4 Pro launched in April 2026 at $1.74/$3.48 per million tokens with a 75% discount, which DeepSeek made permanent in May – the $0.435/$0.87 rates above are the current list prices. From August 16, 2026 the API moves to 2× peak-hour pricing during two daily windows around Beijing time. As with every AI vendor, prices and limits change often; the chart above reflects August 2026 and DeepSeek’s pricing page is the source of truth.
Frequently asked questions
Heads-up:DeepSeek moves fast – models, API ids, and prices change frequently, and the details above reflect August 2026. Check DeepSeek’s official API docs and pricing page for current availability and rates, and treat any claimed R2 timeline as rumor until it actually ships.