Alibaba Cloud
Qwen
Strong multilingual generalist.
Overall Ecological Impact Grade
Not yet scored
A = lowest ecological impact · F = highest ecological impact
Pedigree Snapshot
Founder
Jack Ma
Alibaba co-founder; Qwen is developed by Alibaba Cloud.
Founder Net Worth
$25.9B
Forbes, Sept. 2026
Ownership
Public
Alibaba Group — NYSE: BABA
Regulatory Environment
- USA No comprehensive federal AI law · Voluntary AI Risk Management Framework
- EU AI Act in force
- China Generative AI rules in force
Informational only. DoctorKnow.ai does not advocate for or against legislation, regulation, or political action.
Impact Indicators
Job Displacement
No verified job-loss evidence exists for Qwen3 Max, and no verified Qwen-specific employment-outcome evidence exists at any scope. Reporting on AI-attributed layoffs is industry-level: BBC News documents companies publicly blaming AI for mass job cuts, while Oxford Economics analysis cited by Fortune disputes that AI is the actual cause, pointing instead to weaker demand and cost-cutting. Neither source measures displacement caused by Qwen or Alibaba Cloud, and no causal attribution to either is permitted.
Privacy & Surveillance
No verified data-protection regulator action against Qwen exists — no investigation, finding, enforcement, or settlement is claimed. Available privacy evidence is Alibaba Cloud's own disclosure (the Qwen Cloud Website Privacy Policy and the Qwen Code terms and privacy notice) plus Stanford CRFM's Foundation Model Transparency Index assessment of Alibaba, which measures published disclosure rather than verified internal practice. Independent technical security evidence exists in the CVE Program record CVE-2026-82268 (CNA: VulnCheck, published 2026-08-28), covering Qwen-Agent through v0.0.34; CVE-2026-82275 corroborates the same component. These are software vulnerabilities in Qwen-Agent, not evidence about how hosted Qwen3 Max handles data, and no confirmed exploitation is claimed.
Water Usage
No measured water figure exists for Qwen3 Max, for any Qwen model, or for Qwen Chat. What is disclosed is company- and infrastructure-level: Alibaba Group reports consolidated total water consumption of 13,479,552 m³ for the year ended March 31, 2025, and 17,464,161 m³ for April 1, 2025–March 31, 2026. Alibaba Cloud reports self-built data-centre water usage effectiveness of 1.144 L/kWh (FY2025) and 1.198 L/kWh (FY2026), with reclaimed water of 40,625 m³ at Zhangbei and Ulanqab (FY2025) and 135,858 m³ at Ulanqab (FY2026). WUE is an efficiency ratio, not model water consumption, and it covers self-built sites only — leased capacity is excluded. None of these values is attributable to Qwen.
Energy & Carbon
No independently verified energy or emissions figure exists for Qwen3 Max, for any Qwen model, or for Qwen Chat. Alibaba Group's 2024 and FY2025 ESG reports provide group-level, self-reported emissions and clean-electricity context covering the whole company, not a model. The Carbon Trust study on Alibaba Cloud's carbon benefits was commissioned by Alibaba Cloud and is modeled data-centre scenario analysis, not metered consumption and not model-specific. GPU counts, FLOPs, capital spending, installed capacity, and contracted power are not converted into energy or emissions figures here.
U.S. reporting requirements do not yet provide standardized, model-level disclosure for many AI human and environmental impacts. When U.S. evidence is incomplete, DoctorKnow uses verifiable EU regulatory disclosures, public-sector data, independent research, and reputable journalism to provide the strongest evidence currently available.
Evidence scope is identified as model-specific, provider-level, facility-level, regional/grid, or industry-level.
Value alignment
43/100
Performance fit
87/100
Powered by: Qwen3 (Alibaba)
Scores use a 0–100 scale. Higher scores indicate stronger performance or lower concern; 100 is the best possible rating.
Reasoning
88
Coding
86
Writing
88
Analysis
86
Speed
85
Scores use a 0–100 scale, where 100 represents the strongest outcome and 0 the weakest.
What Qwen does
Qwen is built by Alibaba Cloud and is positioned for multimodal, chat and writing. Our readings score it strongest on multi-step reasoning and long-form writing.
Its weakest measured axis is response speed (85/100), so plan around that when the work depends on it. Access is freemium, and the weights are closed, so you can only reach it through the vendor's own service.
Ethical stance
Transparency reads 49/100. Some model cards and evaluations are public, but training data and methods are only partly described.
Labor and job-displacement posture reads 40/100. There is partial disclosure on data work and workforce impact, with clear gaps.
Regulatory posture reads 33/100. The vendor's public posture leans against binding oversight.
Privacy and data handling
Privacy and data handling reads 41/100. Training opt-out and retention controls exist, but defaults or consumer tiers are less protective.
Because the weights are closed, every prompt is processed on vendor infrastructure — treat regulated or confidential data accordingly.
Energy, carbon and water
Carbon footprint reads 52/100. The energy mix is mixed, and disclosure covers some but not all serving regions.
Water and local impact reads 44/100. Some sites use evaporative cooling in regions with moderate water stress.
Speed and efficiency also matter here: a 85/100 speed reading means fewer compute-seconds per answer for routine work.
Diagnostic notes
Coal-heavy regional grid exposure across several compute regions.
Readings are DoctorKnow.ai's own 0–100 assessments, compiled from vendor documentation and public reporting, and revised as new disclosures land. They are a comparison aid, not a certification.