Small print.
Wide open.

Table of Contents

Our Core Advantages

Mission  &  Focus.  All  of  our  efforts  are  guided  by  a  singular  focus  on  our  mission.  This  focus  enables  us  to 
concentrate  talent,  research,  and  compute  investment  on  the  highest-value  work  for  humanity  and  to  avoid 
conflicting priorities. Achieving our mission means the world gains the enormous benefits of frontier AI while 
mitigating the most significant risks, and we believe this requires safety and capability to advance together.

Talent  &  Culture. Our  mission  and  focus  enable  us  to  attract  and  retain  world-class  talent,  including 
researchers and engineers who want their work to shape a better future. We also have a culture that promotes a 
low-ego,  truth-seeking  environment,  where  frontier  AI  capability  and  safety  are  mutually  reinforcing.  We 
believe our culture has driven our talent density as we have scaled. 

Frontier  &  Safety  Research.  We  believe  that  sustained,  focused  research  at  the  frontier  of  intelligence  is 
required  to  build  the  most  capable  and  safest  AI  systems.  Our  frontier  capabilities  and  safety  research  are 
deeply integrated and directly shape model design, training, and deployment, helping us produce systems that 
are  more  reliable,  steerable,  and  well-suited  for  real-world  deployment,  particularly  in  demanding  enterprise 
environments.  We  translate  our  research  leadership  into  innovation  velocity,  and  have  consistently  released 
better  models,  platform  capabilities,  and  applications.  Each  version  of  a  Claude  model  assists  in  building  the 
next,  helping  to  compress  development  timelines  and  produce  compounding  improvements  in  the  speed  at 
which we innovate. We refer to this recursive dynamic as “closing the loop,” and we believe it is one of the most 
significant structural advantages in frontier AI and can greatly accelerate the rate at which capabilities advance. 
We  believe  that  model  capabilities  must  be  advanced  together  with  safety,  alignment,  and  security  practices, 
particularly as the speed of AI development accelerates. We assess the risks of each model during development 
and before and after release, and take the steps we believe are appropriate to balance model capabilities with 
safety,  alignment,  and  security,  even  where  doing  so  may  moderate  the  rate  at  which  we  release  new 
capabilities.  We  view  decisions  of  this  kind  as  deliberate  tradeoffs  that  we  make  because  they  serve  the 
Company  Purpose,  the  long-term  interests  of  our  mission,  and  our  customers’  demand  for  safe  and  aligned 
models.

Our Approach to Compute. We manage compute as a single, fungible pool from multiple strategic partners, and 
we dynamically direct available compute between workloads based on where the marginal unit is expected to be 
most  productive  at  any  given  time.  We  believe  that  this  approach  to  compute  enables  us  to  deliver  superior 
models, serve more customers, and achieve greater productivity from our compute investment. This compute 
efficiency creates the foundation for us to advance the frontier of AI capabilities through research and model 
development,  meet  growing  demand  from  customers,  and  provide  for  internal  usage  of  Claude.  We  have 
achieved  this  through  our  research  breakthroughs  and  our  multi-chip  compute  architecture  across  AWS 
Trainium, Google TPUs, NVIDIA GPUs, and AMD GPUs, enabling us to orchestrate workloads to optimize for 
price and performance. To support our research, model development, customer demand, and internal usage of 
Claude,  we  continue  to  invest  at  scale.  As  of  and  subsequent  to  September  30,  2026,  we  have  entered  into 
purchase  commitments  and  lease  agreements,  including  short-term  commitments,  as  well  as  leases  not  yet 
commenced, with an aggregate committed spend of more than $          , substantially all of which is related to 
compute and infrastructure. These commitments include approximately $           expected to be incurred before 
December 31, 2030, and substantially all of the remainder is expected to be incurred between 2031 and 2045. 
Approximately  $                     of  these  commitments  are  due  in  the  next  12  months.  See  the  section  titled 
“Management’s  Discussion  and  Analysis  of  Financial  Condition  and  Results  of  Operations—Liquidity  and 
Capital Resources—Contractual Obligations” for more information.

Enterprise Strategy. Our enterprise strategy is built on the belief that frontier AI is most valuable in real-world 
settings,  as  deployment  across  enterprises  is  where  economic  impact  is  greatest  and  where  the  improvement 
loops from customer feedback are richest. Accordingly, we have organized our research priorities, our product 
roadmap, and our go-to-market and Applied AI teams around enterprise use cases, which range from routine 
knowledge  work  to  the  most  complex  problems.  The  customer  feedback  we  gather  directs  our  research  focus 
and makes Claude more capable over time. This broadens where Claude can be deployed and further expands 
enterprise adoption, which helps ensure that the benefits of our AI reach people and organizations at scale. 

180