China AI Statistics and Insights 2026
Here is a comprehensive overview of China's AI statistics, featuring key data and insights you need to know
Overview of China’s AI Landscape
| Dimension | Key Metrics |
|---|---|
| Market Position (2025) | • 1,509 LLMs released (40% of global total) • #1 globally in model releases • $140 billion industry value (2025) |
| Model Philosophy | • Open-source strategy dominant • 9 of top 14 global models are Chinese and open source compared to USA with 0 open source models in top 14. • 180,000+ derivatives created from Qwen alone |
| User Adoption (2025) | • 515 million AI users (June 2025) • 36.5% national penetration rate • Doubled in 6 months • 74.6% under age 40 |
| Cost Efficiency | • 82% lower CapEx than U.S. ($124B vs $694B) • 90% of U.S. model performance • Training costs: $294K-$5.58M vs $100M+ • API pricing: $0.30-$2.50 vs $4.50-$15 per million tokens |
| Investment & Funding | • 48% of global AI funding (2017) • $500B government guidance funds target • 71 AI unicorns (26% of global total) • First AI IPOs globally (Zhipu, MiniMax) |
| Infrastructure | • 5,300+ AI companies (15% of global) • 54% revenue growth in foundational infrastructure • 800+ million internet users (98% mobile) • Near-universal mobile payment adoption |
| Technology Leadership | • 1,576,000 AI patents (38.6% global share) • Top 6 open models globally are all Chinese • 14 of top 20 models on leaderboards • Leading in MoE architecture innovations |
| Talent & Education | • 1,288,999 STEM degrees annually • 39,000 AI researchers • 25% with 10+ years experience • Active global talent recruitment |
| Global Reach | • 17-30% of global model usage • 80% of U.S. open-source startups use Chinese models • 600+ million Qwen downloads worldwide • 10%+ market share in 30 countries |
| Release Velocity (2024/2025) | • New model every 20 days (Alibaba) • Monthly releases (DeepSeek historical) • 500+ models in 2024 alone • 57% faster than U.S. competitors |
| Strategic Sectors | • Security & surveillance (advanced) • E-commerce & retail (dominant) • Transportation/autonomous vehicles (infrastructure-heavy) • Finance & banking (mature) • Healthcare (expanding) |
| Competitive Advantage | • Top-down government support • Largest consumer data repository • Closed-loop domestic ecosystem • Aggressive low-cost pricing • Open-source as strategic weapon |
Key Insight: China has established itself as the world’s leading open-source AI powerhouse, releasing 40% of global LLMs with a strategic commitment to open-weight models that contrasts sharply with U.S. closed-source dominance, while achieving 90% of frontier performance at 82% lower cost through government-coordinated investment, massive user data, and rapid iteration cycles across 5,300+ companies serving 515 million users.
Chinese AI Company Valuations (2025)
| Company | Valuation | Recent Funding | Funding Round | Investor Type |
|---|---|---|---|---|
| Moonshot AI | $4.3 billion | Major round | Series C+ | Alibaba, Tencent, VCs |
| DeepSeek | Not disclosed | Self-funded | N/A | Private/state-backed |
| Zhipu AI | IPO planned | $558 million | Hong Kong IPO | Public markets |
| MiniMax | IPO completed | $620 million | Hong Kong IPO | Public markets |
Key Insight: Chinese AI startups Zhipu and MiniMax raised $558 million and $620 million respectively in Hong Kong IPOs in 2025, becoming the first AI companies globally to go public, while Moonshot AI reached a $4.3 billion private valuation.
Chinese AI Model Adoption by Country (2025)
| Region | Chinese Model Market Share | Number of Countries (>10% share) | Number of Countries (>20% share) |
|---|---|---|---|
| Global Average | 13% | 30 countries | 11 countries |
| United States | 13-17% | N/A | N/A |
| Europe | 10-15% (estimated) | Multiple | Several |
| Asia-Pacific | 20-35% (estimated) | Majority | Many |
| Developing Markets | 25-40% (estimated) | Most | Significant |
Key Insight: Chinese AI models captured over 10% market share in 30 countries and over 20% in 11 countries within months of their release, demonstrating rapid global penetration beyond China’s borders.
Major Chinese AI Model Releases (2024-2025)
| Company | Model Name | Parameters | Release Date | Key Features | License Type |
|---|---|---|---|---|---|
| Alibaba | Qwen 2.5 | 0.5B – 72B | September 2024 | Multi-lingual, multimodal | Open Source (Apache/MIT) |
| Alibaba | Qwen3-Coder | 32B | July 2025 | Advanced code generation | Open Source |
| Zhipu AI | GLM-4.5 | 355B | July 2025 | MoE architecture | Open Source |
| Zhipu AI | GLM-4.5-Air | 106B | July 2025 | Lightweight MoE | Open Source |
| DeepSeek | DeepSeek V3 | 250B (37B active) | Late 2024 | High-efficiency MoE | Open Source |
| DeepSeek | DeepSeek R1 | 671B (37B active) | February 2025 | Reasoning-optimized | Open Source |
| Moonshot AI | Kimi K1 | 20B+ | 2024 | 128K context window | Closed initially |
| Moonshot AI | Kimi K2 | NA | July 2025 | Enhanced coding/reasoning | Open Source |
| MiniMax | MiniMax-01 | NA | January 2025 | Low-cost, open-source | Open Source |
| Baidu | Ernie (latest) | NA | June 2025 | Free to users | Open Source (2025) |
Key Insight: Chinese companies released the majority of their flagship AI models as open-source between 2024-2025, with parameters ranging from 0.5B to 671B, representing a strategic shift toward democratizing AI access.
Chinese AI Model Performance Rankings
| Model | Developer | Type | Performance Score (vs GPT-4) | Special Capabilities | Training Cost |
|---|---|---|---|---|---|
| MiniMax M2 | MiniMax | Open | 90% of GPT-5 | 1M context window | $4.6 million |
| Kimi K2 | Moonshot AI | Open | Matches GPT-5 in coding | 128K context, 65.8% SWE-bench | $4.6 million |
| DeepSeek V3 | DeepSeek | Open | Near GPT-4 level | 37B active params | $5.58 million |
| Qwen3-Coder | Alibaba | Open | Rivals GPT-4 on code | Multi-lingual support | Not disclosed |
| GLM-4.5 | Zhipu AI | Open | Top domestic benchmark | 355B params MoE | Not disclosed |
| DeepSeek R1 | DeepSeek | Open | GPT-4 Turbo level | Advanced reasoning | $294,000 |
Key Insight: Chinese AI models achieved 90% of U.S. frontier model performance while spending 82% less on capital expenditure, this demonstrate remarkable cost-efficiency in AI development.
API Cost Efficiency
| Metric | Chinese Models | U.S. Models | Chinese Advantage |
|---|---|---|---|
| Lowest API Cost | Hunyuan Turbo S: $0.11 input / $0.28 output | gpt-oss-120b: $0.26 (open-source) | Chinese closed models cheaper than U.S. open models |
| Premium Model Cost | Kimi K2: $2.50 output | Claude Sonnet 4.5: $15.00 output | 83% cheaper |
| Blended Cost Leader | Kimi K2: $1.07 blended | Gemini 3 Pro: $4.50 blended | 76% cheaper |
| Best Value Comparison | MiniMax M2: 8% of Claude cost | Claude Sonnet 4.5 baseline | 92% cost reduction |
| Token Efficiency | Qwen: 3.6x more tokens vs GPT-4o-mini | GPT-4o-mini baseline | 260% more processing power per dollar |
| Price Trend | DeepSeek: 62% price reduction (2025) | Stable/increasing pricing | Aggressive price cuts ongoing |
| Market Position | “Lowest in the world” (Chinese APIs) | Higher premium pricing | Global cost leadership |
Key Insight: Chinese AI models achieved global pricing leadership with costs 76-99% lower than U.S. premium models, while DeepSeek’s 62% price reduction in 2025 demonstrates continued aggressive pricing strategies that make Chinese APIs the most affordable worldwide.
Consumer-Facing Chatbot Pricing (Non-API users)
| Chatbot/Platform | Company | Country | Free Tier | Pro/Premium Plan for non-API Chatbot users | Monthly Cost |
|---|---|---|---|---|---|
| ChatGPT | OpenAI | USA | Limited free access | ChatGPT Plus/Pro | $20/month |
| Claude | Anthropic | USA | Very Limited free access | Pro plan | $20/month |
| Gemini | USA | Very generous free access | Plus/Pro/Ultra | $8/month (plus plan) | |
| DeepSeek | DeepSeek | China | Unlimited free access | No premium tier | $0 |
| Ernie Bot | Baidu | China | Free (since April 2025) | No premium tier | $0 |
| Qwen | Alibaba | China | Free | No premium tier | $0 |
| Doubao | ByteDance | China | Free | No premium tier (except for coders) | $0 |
| Kimi | Moonshot AI | China | Free | No premium tier | $0 |
| Yuanbao | Tencent | China | Free | Integrated with WeChat | $0 |
| Baixiaoying | Baichuan Intelligence | China | Free | No premium tier | $0 |
| Zhipu Qingyan (Z.ai) | Zhipu AI | China | Limited free | No premium tier | $0 |
Key Insight: Chinese AI chatbots operate on a free-access model with zero subscription costs for consumers, contrasting sharply with Claude and ChatGPT’s $20/month premium tier, representing a 100% cost advantage that has enabled rapid user adoption (515 million users in China vs 195 million in U.S.).
Major Chinese Tech Company AI Model Release Frequency (2025)
| Company | Average Days Between Releases | Models Released (2025) | Release Strategy |
|---|---|---|---|
| Alibaba | 20 days | 18+ models | Rapid iteration |
| DeepSeek | 30 days (2023-2024) | Monthly releases | Slowed after R1 |
| Zhipu AI | Variable | Multiple versions | Strategic releases |
| Anthropic (US comparison) | 47 days | Fewer releases | Slower cadence |
| Moonshot AI | Variable | K2 series | Focused updates |
| ByteDance | 30-45 days | Kimi series | Steady pace |
Key Insight: Alibaba released new AI models every 20 days on average in 2025, maintaining a pace 57% faster than U.S. competitor Anthropic’s 47-day average between releases.
U.S. Startup Adoption of Chinese AI Models
| Metric | Percentage/Number | Context | Year |
|---|---|---|---|
| AI startups using open-source | 20% of total | Baseline population | 2025 |
| Of those, using Chinese models | 80% | Of open-source users | 2025 |
| Overall Chinese model usage | 16% | All U.S. AI startups | 2025 |
| Notable adopters | Airbnb, Pinterest, others | Fortune 500 companies | 2025 |
Key Insight: Approximately 80% of U.S. AI startups using open-source models chose Chinese alternatives in 2025, with major companies like Airbnb reporting heavy reliance on Alibaba’s Qwen for its speed and cost-effectiveness.
Chinese vs USA AI Model Usage (2024-2025)
| Time Period | Chinese Models (% Global Usage) | U.S. Models (% Global Usage) | Growth Rate (Chinese) |
|---|---|---|---|
| Late 2024 | 1.2% | 75% | Baseline |
| Q1 2025 | 13% (2-month surge) | 65% | +983% |
| Mid-2025 | 17% (downloads) | 15.8% (downloads) | +1,317% |
| August 2025 | 30% | 50% | +2,400% |
| End 2025 | 35-35% | 45-55% | Sustained high |
Key Insight: Chinese AI models grew from 1.2% to 30% of global usage in just 12 months, representing a 2,400% increase and overtaking U.S. models in open-source downloads by mid-2025.
Chinese AI Industry Growth and 2030 Target
| Metric | 2024 | 2025 | 2030 Goal |
|---|---|---|---|
| AI Industry Value (USD) | $126.7 billion | $140 billion | $150.8 billion (core) + $1.5 trillion (related) |
| Year-over-Year Growth | 24% | 20-25% | N/A |
| Number of AI Companies | 5,100+ | 5,300+ | Significant expansion |
| Share of Global AI Companies | 15% | 15%+ | Leadership target |
| Number of AI Unicorns | 71 | 75+ | Major increase |
| Share of Global AI Unicorns | 26% of 271 total | 28% | 35%+ |
Key Insight: China’s AI industry scaled to $126.7 billion in 2024 with 24% year-over-year growth, housing 15% of global AI companies and 26% of the world’s AI unicorns, positioning it as the second-largest AI economy globally.
Chinese AI Infrastructure Segments (2024)
| Segment | Revenue Growth (YoY) | Market Focus | Key Players |
|---|---|---|---|
| Foundational Infrastructure | 54% | AI chips, computing power, data centers | Huawei, Cambricon, Alibaba Cloud |
| Model Architecture | 18% | LLMs, training frameworks, algorithms | Baidu, Alibaba, Tencent, DeepSeek |
| Industry Applications | 13% | Healthcare, finance, manufacturing, retail | All major players |
| Smart Hardware | Rapid growth | AI phones, computers, cars | Xiaomi, Baidu, startups |
Key Insight: China’s AI foundational infrastructure grew 54% year-over-year in 2024, outpacing model architecture (18%) and applications (13%), reflecting heavy investment in computing capabilities despite U.S. chip restrictions.
China’s AI Model Output vs Global Total
| Time Period | Chinese LLMs Released | Global LLMs Released | China’s Share | China’s Rank |
|---|---|---|---|---|
| By July 2025 | 1,509 | 3,755 | 40.2% | #1 globally |
| By September 2025 | 1,500+ | 3,800+ | 39-40% | #1 globally |
| 2024 alone | 500+ (estimated) | 1,200+ (estimated) | 42% | #1 globally |
Key Insight: China released 1,509 large language models by July 2025, accounting for 40% of all global LLM releases and surpassing every other country, including the United States.
China’s Generative AI User Base Growth
| Time Period | Total Users | Penetration Rate | Population Base | Growth Rate |
|---|---|---|---|---|
| December 2024 | 257 million | 18.2% | 1.41 billion | Baseline |
| June 2025 | 515 million | 36.5% | 1.41 billion | +100% (6 months) |
| Total Growth | +258 million | +18.3 percentage points | Stable | Doubled |
Key Insight: China’s generative AI user base doubled from 257 million to 515 million in just six months (December 2024 to June 2025), achieving a 36.5% national penetration rate and becoming the world’s largest AI user market.
Demographics of Chinese AI Users (2025)
| Age Group | Percentage of Users | Education Level | Percentage of Users | Platform Preference |
|---|---|---|---|---|
| Under 40 | 74.6% | Higher education degree | 37.5% | Domestic platforms |
| 40-50 | 18% | Secondary education | 40% | Mixed platforms |
| Over 50 | 7.4% | Primary/other | 22.5% | Simple interfaces |
| Young professionals | Majority | STEM backgrounds | Significant portion | Multiple platforms |
Key Insight: Young and middle-aged professionals under 40 represent 74.6% of China’s AI user base, with 37.5% holding higher education degrees, indicating AI adoption is concentrated among digitally native, educated populations.
Chinese AI Investment Comparison (2016-2017 Shift)
| Year | Chinese AI Funding | US AI Funding | China’s Share of Global Funding | Total Global Funding |
|---|---|---|---|---|
| 2012 – 2016 | $2.6 billion | $17.2 billion | 11.3% (2016) | $23 billion |
| 2017 | 48% global share | 38% global share | 48% | New records |
| Change | +2,530% increase | Moderate growth | +325% share increase | Major shift |
Key Insight: Chinese AI startups’ share of global funding surged from 11.3% in 2016 to 48% in 2017, representing a 325% increase in market share and overtaking the United States in total AI investment for the first time.
Government Guidance Funds vs Private VC (2016)
| Fund Type | 2016 Fundraising Target | Share of Total Market | Growth Trajectory |
|---|---|---|---|
| Government Guidance Funds (GGF) | $500 billion | Growing dominance | Exceeding private by 2017 |
| Private VC Funds | $330 billion | Traditional majority | Being overtaken |
| Government AI Investment | $1+ billion (direct) | Increasing | Rapid acceleration |
Key Insight: Chinese government guidance funds set a $500 billion fundraising target in 2016, exceeding private VC’s $330 billion target by 51%, signaling the state’s dominant role in AI financing.
AI Model Operational Costs Comparison
| Model | Cost per Million Tokens (Blended) | Developer Country | Model Type | Cost vs GPT-4 |
|---|---|---|---|---|
| Kimi K2 Thinking | $1.07 | China | Open | -76% |
| MiniMax M2 | $2.50 | China | Open | -44% |
| DeepSeek V3 | Low (specific pricing varies) | China | Open | -60-80% |
| Qwen-Plus | $0.30 (estimate) | China | Open | -93% |
| Google Gemini 3 Pro | $4.50 | USA | Closed | Baseline comparison |
| GPT-5 Codex | $15 per million output | USA | Closed | Baseline |
| OpenAI gpt-oss-120b | $0.26 | USA | Open | -94% |
Key Insight: Chinese AI model Kimi K2 operates at $1.07 per million tokens, representing a 76% cost reduction compared to Google’s Gemini 3 Pro, while maintaining comparable performance levels.
AI Model Training Cost Efficiency
| Model | Training Cost | Performance Level | Parameters | Cost Efficiency vs US Models |
|---|---|---|---|---|
| DeepSeek R1 | $294,000 | GPT-4 Turbo level | 671B (37B active) | 99.7% cheaper than GPT-4 |
| Kimi K2 | $4.6 million | Matches GPT-5 coding | Not disclosed | 98.5% cheaper (estimated) |
| MiniMax M2 | $4.6 million | 90% of GPT-5 | 1 trillion (estimates) | 98% cheaper |
| DeepSeek V3 | $5.58 million | Near GPT-4 | 250B (37B active) | 99.4% cheaper |
| GPT-4 (estimate) | $100+ million | Frontier | 1.7 trillion (rumored) | Baseline |
| Llama 4 (estimate) | $300+ million | Frontier | Large | High cost |
Key Insight: DeepSeek trained its R1 model for just $294,000 while achieving GPT-4 Turbo-level performance, representing a 99.7% cost reduction compared to estimated $100+ million GPT-4 training costs.
AI Researcher Pool Comparison
| Country/Region | Number of AI Researchers | Share of Experienced Researchers (10+ years) | Top Universities Count |
|---|---|---|---|
| United States | 78,000+ | 50% | 50+ (world leaders) |
| China | 39,000 | 25% | Growing number |
| Ratio (China/US) | 50% | 50% | Lower concentration |
Key Insight: China’s AI researcher pool of 39,000 is half the size of the U.S.’s 78,000, with only 25% having 10+ years of experience compared to 50% in the U.S., revealing a significant talent gap despite rapid growth.
STEM Education Output Comparison
| Metric | China | United States | China’s Advantage |
|---|---|---|---|
| STEM Degrees Awarded (2014) | 1,288,999 | 500,000 | +158% more |
| Patent Applications (AI-related) | 1,576,000 (by April 2025) | 589,410 | +167% more |
| Share of Global AI Patents | 38.6% | 20-25% | Global leader |
| Academic Papers Published | Higher volume | High quality focus | Quantity advantage |
Key Insight: China awarded 1,288,999 STEM degrees in 2014, producing 158% more graduates than the United States and filing 1,576,000 AI-related patents by April 2025 (38.6% of the global total).
Chinese AI Platform User Base (2025)
| Platform/Model | Monthly Active Users | Company |
|---|---|---|
| Doubao | 100+ million | ByteDance |
| DeepSeek | 130+ million | DeepSeek |
| Ernie Bot | 200+ million | Baidu |
| Qwen | 30+ million | Alibaba |
| Kimi | 100+ million | Moonshot AI |
| WeChat (integration) | 1+ billion | Tencent |
Key Insight: Ernie Bot reached 300 million users while Alibaba’s Qwen achieved 600 million downloads globally by 2025, with WeChat’s 1 billion users providing Tencent’s Yuanbao AI with an unparalleled distribution advantage.
Open-Source Model Derivatives
| Base Model | Number of Derivatives Created | Developer | Download/Usage Metrics |
|---|---|---|---|
| Qwen | 180,000+ | Alibaba | 600+ million downloads |
| DeepSeek | Thousands | DeepSeek | Widespread adoption |
| GLM/ChatGLM | Millions of downloads | Zhipu AI | High community engagement |
| Llama (US comparison) | Significant but slowing | Meta | Being overtaken |
Key Insight: Alibaba’s Qwen family spawned over 180,000 derivative models globally, becoming one of the most adopted open-source LLM families and exceeding Meta’s Llama in download velocity.
Chinese Model Performance in U.S. Benchmarks
| Model | SWE-bench Score | MATH-500 Score | LiveCodeBench | Developer |
|---|---|---|---|---|
| Kimi K2 | 65.8% | 97.4% | 53.7% | Moonshot AI |
| IQuest Coder | 81.4% (Verified) | N/A | 81.1% (V6) | Chinese team |
| DeepSeek V3 | High performance | 96.0% (AIME) | 46.9% | DeepSeek |
| GPT-4.1 (comparison) | Comparable | 92.4% | 44.7% | OpenAI |
| GPT-5 Codex | Leading | 94.6% (AIME) | Leading | OpenAI |
Key Insight: Chinese AI model Kimi K2 achieved a 97.4% score on MATH-500 and 65.8% on SWE-bench, surpassing GPT-4.1’s 92.4% and 44.7% respectively, demonstrating Chinese models’ mathematical and coding superiority in specific benchmarks.
Chinese AI Model Rankings (October 2025)
| Position in Top 20 | Chinese Models | U.S. Models | Notes |
|---|---|---|---|
| 1-5 | 2 | 3 | U.S. holds top positions |
| 6-10 | 4 | 1 | Chinese models dominating |
| 11-15 | 5 | 0 | Chinese majority |
| 16-20 | 3 | 2 | Strong Chinese presence |
| Total in Top 20 | 14 | 6 | China 70%, U.S. 30% |
| Open-source count | 9 (Chinese) | 0 (U.S.) | All Chinese top models open |
Key Insight: Chinese AI models occupied 14 of the top 20 positions on OpenCompass’ LLM leaderboard in October 2025, with 9 being open-source compared to zero open-source U.S. models in the top rankings.
Capital Expenditure Efficiency (2023-2025)
| Region | Total CapEx (2023-2025) | Leading Model Performance | Cost per Performance Point |
|---|---|---|---|
| China (Hyperscalers) | $124 billion | 90% of U.S. level | Highly efficient |
| U.S. (Big Tech) | $694 billion | Frontier (100%) | Higher investment |
| Efficiency Gap | 82% lower Chinese spending | 10% performance gap | 820% cost advantage ratio |
Key Insight: Chinese AI hyperscalers spent $124 billion on AI infrastructure (82% less than U.S. companies’ $694 billion) while achieving 90% of U.S. performance levels, demonstrating an 8:1 cost-efficiency advantage.
China’s AI Implementation Priorities
| Sector | Government Investment | Private Sector Activity | Development Stage |
|---|---|---|---|
| Security & Surveillance | Very high | Extensive | Advanced deployment |
| Healthcare | Growing | Moderate | Expanding rapidly |
| Transportation/Autonomous Vehicles | Very high | Extensive | Infrastructure building |
| Finance & Banking | High | Extensive | Mature deployment |
| E-commerce & Retail | High | Dominant | Leading globally |
| Education | Growing | Expanding | Active development |
| Energy | Moderate | Growing | Early-mid stage |
Key Insight: China prioritizes AI deployment in security, transportation, and e-commerce with extensive government and private sector collaboration, while healthcare receives growing but uneven investment despite the nation’s aging population challenge.
References
DataGlobeHub makes use of the best available data sources to support each publication. We prioritize sources of good reputation, like government sources, authoritative sources, expert sources, and well-researched publications. When citing our sources, we provide the report title followed by the publication name. Where not applicable, we provide just the publication name.
- China’s AI industry thrives with over 5,300 enterprises – State Council of the People’s Republic of China
- More of Silicon Valley is building on free Chinese AI – NBC News
- The 2025 AI Index Report – Stanford University.
- Ranking the Chinese Open Model Builders – Interconnects
- China’s AI models achieve 90% of U.S. performance with fraction of capex – Investing.com
- Low-cost Chinese AI models forge ahead, even in the US, raising the risks of a US AI bubble – Chatham House
- An Overview of Chinese Open-Source LLMs – IntuitionLabs
- Artificial intelligence in China – statistics & facts – Statista
- 8 Chinese AI Tools That Are Better Than ChatGPT – dapengyu
- China’s generative AI user base doubles to 515 million in six months – AI News
- Chinese AI models surge to 30% of global usage as open-source landscape shifts – TechWire Asia
- China tops global AI model count, over 1,500 large models released – China Daily
- China’s AI ambitions target US tech dominance – DW
- Is China quietly winning the AI race? – BBC
- The Top Open AI Models Are Chinese. Arcee AI Thinks That’s A Problem. – Forbes
- US–China AI model costs diverge – fDi Intelligence
- AI in China – Recent History, Strengths and Weaknesses of the Ecosystem – Emerj
- Chinese LLMs vs Western LLMs – Developments, Comparisons, and Global Outlook – INAI We Trust
