For most of the recent AI boom the story was simple: the best models came from a handful of well-funded labs, and competing meant burning enormous sums on chips and compute. Then a comparatively small Chinese company released a model that scored alongside the leaders while costing a tiny fraction to build. The reaction was immediate and dramatic, and it changed how the whole industry talks about cost. This guide explains what DeepSeek is, how it works and what it actually means for your business.
What exactly is DeepSeek?
DeepSeek is an artificial intelligence company based in China that designs and releases large language models, the same broad family of technology that powers the AI assistants most people have already tried. It grew out of a quantitative investment firm and launched its own research effort in 2023, which gave it both deep technical talent and an unusual willingness to share its work openly. Its standout release, DeepSeek-R1, is a reasoning model tuned to work through problems step by step rather than answering on instinct.
What sets it apart is the open-weight approach. Many leading assistants are closed boxes you can only access through a paid interface, but DeepSeek publishes its model weights under a permissive licence. That means developers anywhere can download the model, inspect how it behaves, fine-tune it for their own needs and run it on their own hardware. For a field that had been drifting toward secrecy, that openness was a genuine shift.
Why did DeepSeek shake the market?
The shock was about money, not just capability. DeepSeek claimed it trained a frontier-class model for a few million dollars in compute, a sum dwarfed by the budgets widely assumed to be necessary. When that claim landed in late January 2025, investors questioned whether the heavy spending baked into chip and infrastructure valuations was still justified, and the market repriced fast.
The numbers were stark. In a single trading session, one major chipmaker shed close to 600 billion US dollars in value, described at the time as the largest single-day loss in market value for any company in history (Reuters). The broader sell-off ran into the hundreds of billions more across the sector. The lesson investors took away was that efficiency, not just raw spending, would decide who leads in AI.
How does DeepSeek run so cheaply?
The core trick is an architecture called mixture-of-experts. Instead of running every part of a huge model for every single request, the model is divided into many specialist sub-networks, and a router activates only the few that a given task actually needs. The model can be enormous in total, yet only a small slice of it does work at any moment, which slashes the compute cost of both training and answering.
DeepSeek paired that with clever engineering around how the model is trained and how it handles long inputs, squeezing more capability out of less hardware. The result is a model that thinks carefully through hard problems, such as maths and coding, without the eye-watering running costs usually attached to that level of performance. Efficiency, in other words, became a feature in its own right rather than an afterthought.
How does DeepSeek compare to other assistants?
On everyday tasks, such as drafting, summarising and answering questions, DeepSeek feels much like the other strong assistants on the market. On structured reasoning, where the model has to plan and check its own working, its dedicated reasoning model competes with the best closed systems. The headline difference is not a single benchmark but the combination of open weights and low cost, which together change who can realistically use a top-tier model.
There are trade-offs to weigh honestly. Closed providers often wrap their models in polished tools, enterprise support, content controls and tight integrations that an open model leaves to you. Choosing well means matching the tool to the job rather than chasing a leaderboard, the same disciplined approach we take when we help clients pick between the wider family of AI models for a given use case.
What does it mean for Australian businesses?
The upside is access. Cheaper, openly available models lower the barrier to building real AI features, so a small Australian firm can now afford capabilities that were recently the preserve of large enterprises. AI adoption among Australian businesses has been climbing steadily, with the national statistics agency reporting that a growing share of firms have integrated AI into their operations (Australian Bureau of Statistics). Falling model costs only accelerate that.
The caution is data. The hosted DeepSeek service processes information on overseas servers, which raises privacy and compliance questions for sensitive customer data under Australian rules. Several governments and large organisations have restricted the official app on official devices for exactly that reason. The safer path for most businesses is to self-host the open model or use it through a vetted provider, with clear policies on what data is sent where.
Should your business use DeepSeek?
For experimentation, internal tools and tasks that do not touch sensitive customer data, DeepSeek is well worth a look, especially where cost matters and you want the freedom to self-host. For anything involving personal or regulated information, treat the hosted service with care and design the data flow before you switch anything on. The smart move is to start with a small, well-scoped pilot and measure the results.
Ultimately, DeepSeek matters less as a single product and more as a signal. It proved that capable AI is getting cheaper and more open, which is good news for any business that has been waiting for the technology to become affordable. The winners will be the teams that pair the right model with a clear plan and sensible guardrails, rather than those simply chasing whichever name is in the headlines this month.
Open-weight DeepSeek vs a typical closed assistant
The clearest way to see where DeepSeek differs is to line up its open-weight approach against the closed, proprietary assistants most people have already tried.
| Factor | DeepSeek (open weight) | Typical closed assistant |
|---|---|---|
| Access to the model | Weights published, free to download | Available only through a hosted interface or API |
| Self-hosting | Yes, run it on your own infrastructure | No, you depend on the provider |
| Architecture | Mixture-of-experts, only the needed parts activate | Varies, often a dense or undisclosed design |
| Running cost | Low, efficiency was a core design goal | Typically higher, paid per use |
| Data location | Your servers if self-hosted, overseas if hosted | The provider's servers, often offshore |
| Tooling and support | You assemble your own stack | Polished tools, enterprise support and controls |
Watch: making sense of the AI shift
In short
What is DeepSeek AI?
Key takeaways
- DeepSeek is an open-weight AI model built in China, best known for strong reasoning at a low cost to train and run.
- Its January 2025 launch wiped close to a trillion dollars off tech stocks in a single session, the largest single-day loss for one company on record.
- A mixture-of-experts design activates only the parts of the model a task needs, which is the secret behind its efficiency.
- For Australian businesses the headline is cheaper, more accessible AI, balanced against real questions about data privacy and where information is processed.