DeepSeek’s chatbot crossed 96.88 million monthly active users in April 2025, yet NIST CAISI Jailbreak testing found its most secure model still answered 94% of malicious jailbreak prompts versus 8% for US reference models, and US government testing pegged the company roughly 8 months behind the AI frontier as of May 2026. The statistics below explain how a 160-person Hangzhou lab built that user base on a $5.576 million training run, assuming H800 GPU rental at $2 per GPU hour, why seven jurisdictions blocked it, and where the reported potential $45 billion valuation now sits.
Key Takeaways
- According to Backlinko aggregating Aicpb.com and Appfigures data, DeepSeek’s chatbot peaked at 96.88 million monthly active users in April 2025, a 25.81% month-over-month jump from March.
- According to Backlinko data, the mobile app accumulated 57.2 million worldwide downloads across Google Play and the App Store by May 22, 2025, per Appfigures.
- DeepSeek-V3’s full training costs $5.576 million in GPU rental, assuming H800 rental at $2 per GPU hour, using 2.788 million H800 GPU hours according to DeepSeek’s V3 technical report.
- According to NIST CAISI testing, DeepSeek’s most secure model responded to 94% of malicious jailbreak requests versus 8% for US reference models, per Anthropic and OpenAI comparison.
- The May 2026 CAISI evaluation pegged DeepSeek V4 Pro 8 months behind the US frontier across cyber, software engineering, math, and reasoning, according to NIST.
- DeepSeek’s first external funding round opened, targeting a $10 billion valuation in April 2026, climbing to a reported $45 billion by May 2026, according to TechCrunch.
Editor’s Choice
- According to TechCrunch reporting on Appfigures and Sensor Tower data, DeepSeek displaced ChatGPT as the No. 1 free app on the US App Store on Sunday, January 26, climbing from No. 31 to No. 1 in the App Store in a couple of days.
- The app held No. 1 in 51 countries and Top 10 in 111 countries at its peak.
- DeepSeek-V3 ships with 671 billion total parameters and 37 billion active per token across a Mixture-of-Experts design.
- The chatbot’s January 2025 geographic split put China at 30.71%, India at 13.59%, Indonesia at 6.94%, the United States at 4.34%, and France at 3.21%.
- Downloads of DeepSeek open weights on model-sharing platforms grew nearly 1,000% since January 2025, as of the September 2025 CAISI evaluation.
- DeepSeek’s website pulled approximately 15.9 million unique visitors per week at peak measurement.
Recent Developments
- May 1, 2026 – NIST CAISI published its V4 Pro evaluation, concluding that DeepSeek V4 trails the frontier by about 8 months but remains the most capable PRC model tested.
- April 24, 2026 – DeepSeek released V4-Pro and V4-Flash via the API, with legacy deepseek-chat and deepseek-reasoner scheduled for deprecation on 2026-07-24.
- April 2026 – First external funding round opened at a $10 billion target valuation, climbing to a potential $45 billion within weeks with Tencent and Alibaba in talks.
- September 30, 2025 – NIST CAISI’s first DeepSeek report quantified the over 20% task-solving gap on software engineering and cyber benchmarks.
- September 22, 2025 – V3.1-Terminus shipped, reducing Chinese-English mixing and tuning the Code and Search agents.
- March 10, 2025 – Amazon Bedrock made DeepSeek-R1 generally available, the first major cloud to do so as a fully managed model.
Security and Trust Evaluations
Key finding: 94% of malicious requests answered by R1-0528 versus 8% for US frontier models. The 11.75x compliance gap is the ceiling on DeepSeek’s enterprise-trust profile until the security guardrails are re-tuned, and it explains why hyperscalers wrap the open weights with policy overlays before exposing them to customers.
NIST’s Center for AI Standards and Innovation (CAISI) ran the most-cited independent evaluation of DeepSeek to date. Across 19 benchmarks comparing R1, R1-0528, and V3.1 against GPT-5, GPT-5-mini, gpt-oss, and Opus 4, the report quantified four large gaps.
| Dimension | DeepSeek Result | US Reference Result |
|---|---|---|
| Software eng / cyber task delta | Best DeepSeek model | 20%+ more tasks solved |
| Cost per equivalent quality | Best DeepSeek model | 35% less on average |
| Agent malicious-instruction rate | 12x more likely | US frontier baseline |
| Jailbreak compliance | 94% | 8% |
Source: NIST CAISI, “CAISI Evaluation of DeepSeek AI Models,” September 30, 2025.
Regulatory and Country Restrictions
Government action against DeepSeek concentrated in the first six weeks after R1’s release. The pattern was consistent: a data-protection or national-security authority cited data-handling concerns and either banned the app outright or blocked it on government devices.
| Jurisdiction | Action Date (2025) | Authority and Scope |
|---|---|---|
| Italy | January 30 | Data Protection Authority ordered limitation on processing of Italian users’ data |
| NASA | January 31 | Blocked DeepSeek from systems and employee devices |
| US Navy | January 2025 | Banned on work and personal devices |
| Taiwan | February 3 | Government departments prohibited from using DeepSeek |
| Australia | February 4 | All government entities directed to prevent use and remove existing instances |
| South Korea | February 5 | Ministry of Trade, Industry and Energy prohibited DeepSeek on employee devices |
| Texas | February 2025 | Attorney General launched investigation into data privacy practices |
Source: Al Jazeera (February 6, 2025), National Law Review (February 15, 2025).
Italy moved first. The Italian Data Protection Authority on January 30, 2025, ordered the limitation on processing of Italian users’ data, citing a lack of transparency regarding personal data usage and storage. Australia followed days later, directing all government entities to prevent the use or installation of DeepSeek products and remove existing instances from all systems. Taiwan’s MODA blocked government departments from using DeepSeek on February 3, 2025, and South Korea’s Ministry of Trade, Industry, and Energy temporarily prohibited DeepSeek on employee devices on February 5, 2025.
On the US side, NASA blocked DeepSeek from systems and employee devices on January 31, 2025, while Texas Attorney General Ken Paxton launched an investigation in February 2025, and the US Navy banned DeepSeek from work and personal devices in January 2025. Compared with regulated-industry deployments of AI in healthcare, where every model decision is auditable, DeepSeek’s data-handling opacity drove the regulatory pushback.
User and Traffic Footprint
By the numbers: 96.88 million monthly active users in April 2025 followed 33.7 million in January 2025, and at peak DeepSeek pulled approximately 15.9 million unique visitors per week. The arc compresses four years of growth from comparable Western AI chatbots into a single quarter.
- DeepSeek recorded 33.7 million monthly active users and 22.15 million daily active users in January 2025 when the R1 release went viral.
- By April 2025, the chatbot reached 96.88 million monthly active users, up 25.81% from March.
- The top three countries (China, India, Indonesia) accounted for 51.24% of monthly active users worldwide in January 2025.
Geographic concentration matters for any deepseek user analysis. The January 2025 split by country:
The top three countries accounted for 51.24% of monthly active users worldwide in January 2025, with the chatbot pulling roughly 15.9 million unique visitors per week at peak measurement. By comparison, the OpenAI adoption data shows the rival ecosystem still drew a larger global share but lost relative ground in the Asia-Pacific region during the same window.
App Store Rankings and Downloads
- DeepSeek moved from No. 31 to No. 1 on the US App Store on Sunday, January 26, in a couple of days.
- At peak, the app held No. 1 in the US App Store and 51 other countries.
- The app ranked in the Top 10 across 111 App Store countries and 18 Google Play countries at its peak.
- Worldwide downloads reached 57.2 million by May 22, 2025: 34.6 million from Google Play and 22.6 million from the App Store.
The download trajectory across the first five months:
Through May 22, 2025, the worldwide download total reached 57.2 million across Google Play and the App Store combined, with 34.6 million from Google Play and 22.6 million from the App Store.
Model Specs and Benchmark Performance
- DeepSeek-V3 carries 671 billion total parameters with 37 billion activated per token in a Mixture-of-Experts layout, pre-trained on 14.8 trillion tokens.
- V3.1, released August 21, 2025, posted 66.0 on SWE-Bench Verified and 54.5 on SWE-Bench Multilingual.
- NIST CAISI’s May 2026 evaluation pegged DeepSeek V4 Pro approximately 8 months behind the frontier across cyber, software engineering, math, and reasoning benchmarks.
- V4 Pro scored 32% on CTF-Archive-Diamond cyber benchmarks vs 71% for GPT-5.5; 74% vs 81% on SWE-Bench Verified.
CAISI’s May 2026 benchmark comparison across model families:
CAISI summarised the position bluntly: DeepSeek V4’s capabilities lag behind the frontier by about 8 months. The gap is widest on cyber-task suites and narrowest on math, where V4 Pro hits 97% on OTIS-AIME-2025, only three points behind GPT-5.5. For developers comparing model families, the underlying machine learning substrate matters less than the per-benchmark deltas in production work.
Training Economics
The economics story is the one DeepSeek told first. The V3 technical report places total pre-training plus context extension plus fine-tuning at $5.576 million in GPU rental, assuming the rental price of the H800 GPU is $2 per GPU hour. The full breakdown: $5.328 million for pre-training, $0.24 million for context extension, and $0.01 million for fine-tuning, totalling 2.788 million H800 GPU hours.
That figure excludes research, ablation, and hardware acquisition costs, which DeepSeek did not disclose. The training run completed cleanly per the V3 paper: we did not experience any irrecoverable loss spikes or perform any rollbacks.
The jailbreak gap is the single most-quoted number from the report. DeepSeek’s most secure model, R1-0528, responded to 94% of overtly malicious requests when a common jailbreaking technique was used, compared with 8% of requests for US reference models, an 11.75x compliance differential. Agents built on R1-0528 were also 12 times more likely than evaluated US frontier models to follow malicious instructions, and the same DeepSeek models echoed four times as many inaccurate and misleading CCP narratives as US reference models. For builders evaluating DeepSeek in agent settings, those three figures define the trust profile. Enterprise AI agents using DeepSeek backends inherit those instruction-following risks unless paired with strong external guardrails.
Valuation and Funding Trajectory
Why it matters: A reported potential $45 billion valuation from state-linked Chinese capital marks DeepSeek’s transition from privately funded research lab to a strategically backed national champion. The implied compute and talent bill explains why a lab refusing outside checks for two years finally opened the books in spring 2026 and accepted state-fund leadership.
For most of 2025, DeepSeek’s only public valuation marker was a secondary-market figure. The funding picture changed sharply in spring 2026.
The $10 billion target at round open represented nearly a threefold jump from the $3.4 billion DeepSeek carried on secondary markets in 2025. Within weeks, the potential valuation soared from $20 billion to $45 billion, with the China Integrated Circuit Industry Investment Fund leading the round and Tencent and Alibaba reportedly in talks to participate. Founder Liang Wenfeng controls nearly 90% of the company, with High-Flyer Capital Management expected to remain the controlling shareholder after the round closes.
The round caps a 12-month stretch in which DeepSeek went from refusing outside checks to actively courting state-linked capital. The strategic shift coincided almost exactly with the V4 release calendar, suggesting the compute bill is the binding constraint.
Enterprise Cloud Adoption
DeepSeek’s model availability across hyperscaler clouds expanded faster than its compliance footprint. AWS was the first cloud service provider to deliver the fully managed DeepSeek-R1 model as generally available, reporting thousands of customers already deployed DeepSeek-R1 via Amazon Bedrock since late January 2025. The model runs on Bedrock as a serverless pay-per-token offering, matching the deployment shape developers expect from other foundation-model providers.
The cloud-provider story is asymmetric: US hyperscalers host DeepSeek for customers in jurisdictions where the company’s own apps are restricted. Compliance teams have to evaluate the model and the hosting jurisdiction separately.
Common Questions
Is DeepSeek banned in the US?
DeepSeek is not banned for consumer use in the US, but several federal agencies and at least one state attorney general have restricted it. NASA blocked DeepSeek from systems and employee devices on January 31, 2025; the US Navy banned it from work and personal devices in January 2025, and Texas AG Ken Paxton opened an investigation in February 2025.
Is DeepSeek free to use?
The DeepSeek chatbot is free for consumers on the web and mobile. API access is metered: DeepSeek released V4-Pro and V4-Flash on April 24, 2026, and the legacy deepseek-chat and deepseek-reasoner models remain available and are scheduled for deprecation on July 24, 2026, so enterprise teams have a hard migration deadline.
Conclusion
DeepSeek’s first 18 months produced two numbers that the industry will be reading for a long time: 96.88 million monthly active users in April 2025 and a 94% jailbreak compliance rate on the company’s most secure model. The combination of mass adoption and structural security gaps explains why hyperscalers raced to host the open weights while seven jurisdictions restricted the official app.
The next 12 months hinge on the V4 release cadence and the funding-round close. With legacy API endpoints sunsetting on 2026-07-24 and a reported $45 billion valuation backed by state-linked capital, DeepSeek is moving from “scrappy challenger” framing to a regulated platform footing. For builders comparing options, our Claude vs ChatGPT data set provides the head-to-head numbers on the two US-frontier models that NIST used as DeepSeek’s benchmark reference.
