DeepSeek
Frontier-level answers for free — the open-weight models that shook the market.
Standout features
DeepSeek’s pitch is value — strong reasoning and coding, free in the app and cheap by API, with open weights you can self-host.
Worldwide search interest, indexed 0–100 · Google Trends.
DeepSeek is the value disruptor — near-frontier capability with open weights and almost no cost.
- Open weights you can self-host.
- A reasoning mode that rivals expensive models.
- Free in the app; cheap by API.
- Trained remarkably efficiently.
DeepSeek punches far above its price.
- Competitive coding and reasoning benchmarks.
- Open-weight R1 / V-series models.
- Self-hosting for full data control.
- Rapid release cadence.
Free in-app, usage-based by API.
DeepSeek is for the cost- and control-conscious.
- Developers optimising cost per token.
- Anyone wanting to self-host open weights.
- Users on tight or zero budgets.
- Organisations with China-origin data policies.
- People wanting a deep consumer tool surface.
No tool is perfect — the trade-offs to weigh:
- China-based — a policy factor for many orgs.
- Content filtering on sensitive topics.
- Thin consumer tool surface vs the giants.
- Privacy review needed for the hosted app.
- ✓Open weights you can self-host
- ✓Reasoning that rivals costly models
- ✓Free app, very cheap API
- ✓Remarkably efficient training
- ✓Fast, disruptive release cadence
- ✕China-based (a policy factor for many)
- ✕Filtering on sensitive topics
- ✕Thin consumer tool surface
- ✕Hosted-app privacy needs review
DeepSeek stunned the market by matching far pricier models for free, and developers especially praise the open weights, low API cost and strong reasoning mode. The caveats are consistent: its China origin raises policy questions for many organisations, sensitive-topic filtering is noticeable, and the consumer toolset is thin. On pure value, sentiment is very high; on enterprise fit, it depends on policy.
DeepSeek is built by DeepSeek, a Chinese AI lab (spun out of quant fund High-Flyer) known for efficient, open-weight models.
Company figures are drawn from public disclosures and reputable trackers (gathered Jun 2026). User and revenue numbers are estimates and move fast.
Pick up to two other coding tools to see them head-to-head on the same rubric.