Current status
Has AI cured cancer yet?
Last checked: today
Nudging technocrats towards the more important benchmarks, in a language they already understand.
Tracker result
No.
Status change: none
CB CancerBench
The frontier remains at zero.
CancerBench measures whether an AI system has cured a cancer. It is currently the most difficult benchmark in AI—harder than DeepSWE, Humanity’s Last Exam or SkateBench—with every frontier model scoring 0%. We have even open-sourced the dataset and are encouraging every frontier lab to benchmaxx it.
CancerBench score
Frontier models · pass@1
Frontier score over time
Best score by model availability
CancerBench score vs. model cost
CancerBench score · Artificial Analysis blended price
Benchmark questions Research objectives 80 questions
| ID | Question | Best score |
|---|---|---|
| Loading the open dataset… | ||
What is working
AI updates
New model beats every benchmark
Cancers cured: 0
AI discovers a drug candidate
Years of human trials begin
CEO declares medicine transformed
Clinical evidence pending
Another “breakthrough” press release
Patients treated: not stated
Researcher updates
A computer-designed drug candidate has reached an early human trial. Researchers developed it; clinicians and trial participants now have to find out whether it is safe or works. The trial is recruiting and has no results.
ClinicalTrials.gov ↗AI-assisted tools may have informed successful treatment for individual patients. Clinicians treated those patients. Remission means the cancer is currently undetectable; a cure means it will never return.
Cure vs remission, NCI ↗Decades of human research have made some cancers routinely curable. Low-stage testicular cancer cure rates approach 100% with established treatments.
Testicular cancer treatment, NCI ↗The NCI sees promise for AI across cancer care. Researchers, clinicians and patients must still establish any clinical benefit through randomized trials.
AI and cancer, NCI ↗Researchers turn candidate molecules into medicine through laboratory work, clinical trials and patient care.
A model may supply a candidate to a human process in which researchers design the studies, clinicians deliver the care and patients take the risk, but the gigafactory gets the headline.