Some links on this page are affiliate links: if you buy through them we may earn a commission, at no extra cost to you.
The headline goes further than the evidence. Microsoft CEO Satya Nadella did call self-declared artificial general intelligence (AGI) milestones “nonsensical benchmark hacking,” but he did not say OpenAI is permanently incapable of achieving AGI. The available evidence points instead to skepticism about narrow AGI claims, reported disagreement over the timing of OpenAI’s contractual AGI threshold, and a larger fight over Microsoft’s rights in the partnership.
What Nadella actually said
In a February 19, 2025 interview with Dwarkesh Patel, Nadella criticized the idea that an AI company can simply announce an AGI milestone after obtaining a particular benchmark result. He described “self-claiming some AGI milestone” as “nonsensical benchmark hacking.”
His preferred test was practical rather than declarative: whether AI produces major productivity gains and helps drive roughly 10% growth in the global economy. Nadella discussed new workflows and the effect of AI on economic output, rather than treating a laboratory score or company announcement as conclusive proof of AGI.
That is not a rejection of AI progress. It is a rejection of using a self-selected label—or a narrow test—as the final measure of success. As The Register reported, Nadella was emphasizing deployment and economic impact.
#1 Best Overall
Does Microsoft believe OpenAI cannot achieve AGI?
There is no public evidence in the cited material for that literal conclusion. The stronger claim appears to be an interpretation of two related but distinct stories.
- Nadella publicly questioned whether self-declared AGI milestones are meaningful.
- Later reporting said Microsoft did not expect OpenAI to satisfy the partnership’s AGI condition before 2030.
The second point is a timing forecast, not a statement that OpenAI will never achieve AGI. The Information reported that Microsoft expected OpenAI would not be able to declare AGI before 2030, while OpenAI executives were reportedly considering whether an earlier declaration was possible.
Those reports described negotiations over restructuring, revenue rights, access to future technology, and the meaning and timing of AGI. They did not establish that Microsoft had formally concluded OpenAI was technically incapable of reaching AGI.
Why the AGI label matters to the partnership
AGI is not merely a philosophical term in the Microsoft–OpenAI relationship. According to reporting summarized by Ars Technica, the agreement gives AGI contractual importance: achieving AGI could affect Microsoft’s access to some future OpenAI technology and other rights under the partnership.
The unusual arrangement turns an imprecise technical concept into a potential commercial trigger. That raises questions such as:
- Who has authority to declare that AGI has been achieved?
- What evidence or tests count?
- Can OpenAI make the declaration unilaterally?
- Does AGI mean broad humanlike capability, economic usefulness, or both?
- Which systems and rights are covered before and after a declaration?
- How would a disagreement be resolved?
The full operative agreement and its adjudication process are not publicly available in the cited sources, so descriptions of its exact legal operation should be treated as reported rather than definitive.
OpenAI’s definition is broader than a benchmark score
OpenAI has been described as defining AGI as highly autonomous systems that outperform humans at most economically valuable work. That is considerably broader than passing a single exam or topping a leaderboard.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →It also remains open to interpretation. “Most economically valuable work” does not mean every intellectual task, and a system can be highly capable while still needing tools, permissions, supervision, or human judgment. Economic performance also depends on deployment: infrastructure, software integration, organizational change, pricing, and labor practices all influence whether a model creates value.
Why benchmarks help—and why they are insufficient
Benchmarks are not worthless. Properly designed tests can provide repeatable comparisons, expose weaknesses, measure progress in coding or mathematics, and make broad claims more testable.
The problem is treating one result as proof of general intelligence. A model can perform well on a familiar or highly optimized test while remaining unreliable in messy, open-ended work. Benchmarks may not reveal:
Rank #3
- Incredibly Light. Surprisingly Thin. - LG gram is designed to go wherever you do. Weighing just 2.5 lbs. with an ultra-slim 0.7-inch profile, it slips easily into your bag and feels light in hand—making it effortless to carry, commute, and work from anywhere.
- Remarkably Light. Reliably Strong. - LG gram has passed seven military-grade durability tests, striking an impressive balance between a highly portable, lightweight metal build and the confidence to handle everyday movement and travel.
- Power That Last with Smart Efficiency - LG gram combines a high-capacity 72Wh battery with AI-driven power management to optimize efficiency based on your usage. The result is up to 32 hours of video playback for} long-lasting performance that keeps up with your day—at home, at work, or wherever you go.
- AMD Ryzen AI Performance - Powered by AMD’s AI-optimized Ryzen processor with Radeon Graphics and a built-in NPU, LG gram delivers smooth multitasking and responsive performance. Fast 32GB LPDDR5x memory and 1TB NVMe storage keep everything moving without slowdowns.
- Dual AI for Always-On Intelligence - LG gram’s Dual AI—powered by EXAONE 3.5, LG’s AI solution—combines gram chat On-Device AI and gram chat Cloud AI to deliver seamless assistance. gram chat On-Device AI enables fast document search and summarization directly on your PC, while gram chat Cloud AI expands capabilities when connected—so everyday tasks stay smooth, responsive, and uninterrupted.
- Long-horizon planning and autonomy;
- Performance on unfamiliar situations;
- Resistance to manipulation and prompt injection;
- Reliability when conditions or data change;
- Accurate tool use across extended workflows;
- Human-review requirements and escalation rates;
- Real economic value after deployment and supervision costs.
Benchmark contamination, narrow optimization, cherry-picked evaluations, and repeated exposure to test formats can further weaken a score’s meaning. Nadella’s “benchmark hacking” criticism is best understood as a warning against using these limitations to manufacture a definitive AGI milestone—not as a claim that every benchmark is invalid.
Free tools Windows power users keep installed
One-click scans. No signup required.
The 10% economic-growth test has limits too
Nadella’s alternative is more grounded in real-world outcomes, but it is not a neutral replacement for capability testing. GDP and productivity are affected by policy, investment, demographics, interest rates, and many technologies besides AI. Gains can take years to appear in official statistics, and a strategically important technology may not immediately produce a visible global growth surge.
Economic impact measures usefulness and diffusion. It does not by itself prove that a system has general reasoning, broad autonomy, or humanlike understanding. Nadella was presenting a business and deployment philosophy, not a universally accepted scientific definition of AGI.
What the reported $100 billion threshold means
Reporting around the partnership described a “sufficient AGI” concept connected to a profit threshold commonly reported as $100 billion. That figure should not be confused with OpenAI’s general definition of AGI or with a scientific test of intelligence.
A profit threshold is a contractual mechanism. Profit depends on pricing, adoption, operating costs, accounting treatment, competition, and market conditions. A system could generate substantial profit without demonstrating every capability associated with general intelligence; conversely, a capable system might not quickly produce that level of profit.
Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteBecause the complete agreement is not public, the threshold and its legal consequences should be described as reported terms rather than settled facts.
The dispute was also about corporate control
The disagreement was not simply a philosophical argument between Microsoft and OpenAI. It involved the timing and meaning of AGI, Microsoft’s continuing access and revenue rights, OpenAI’s proposed corporate restructuring, and the concessions Microsoft wanted before approving changes to the relationship.
That creates an incentive problem. OpenAI could benefit from an earlier AGI declaration if it changed the balance of contractual rights. Microsoft, meanwhile, had a commercial interest in preventing a declaration that it believed would prematurely reduce its access or economic position. Neither side’s preferred interpretation is automatically the same as a scientific consensus.
This is why the story should not be reduced to “Microsoft has lost faith in AI.” Microsoft can believe AI will become extremely valuable, invest heavily in infrastructure and enterprise software, and still doubt that an agreement’s AGI trigger will be reached soon—or that a company’s own announcement is sufficient evidence.
Outdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchWindows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallWhat Microsoft may actually believe
The most defensible reading of the available evidence has three parts:
Best Value
- AI is commercially important now. Nadella’s emphasis on productivity and new workflows reflects confidence in practical AI deployment.
- AGI labels are unreliable as standalone milestones. A narrow benchmark or self-certification does not settle whether a system can perform dependable, broad, autonomous work.
- OpenAI may not meet the partnership’s contractual threshold soon. The reported “before 2030” expectation concerns timing and contract rights, not permanent technical incapability.
Investment in OpenAI also does not require Microsoft to believe that OpenAI will reach a particular AGI definition on a particular date. Cloud demand, model access, enterprise software, and AI services can justify the relationship independently.
What this means for AI customers
For ordinary users, the dispute may have little immediate effect unless negotiations change product availability, pricing, model access, or exclusivity. For enterprises, however, it reinforces a practical lesson: buying AI does not require deciding whether AGI exists.
Organizations should evaluate systems against their own workflows by measuring:
Recommended Free Tools
- Task-completion accuracy on representative data;
- Error rates and human-escalation frequency;
- Total cost per completed workflow;
- Latency, uptime, and capacity;
- Security, retention, and data-governance requirements;
- Auditability and observability;
- Vendor lock-in and the cost of switching models;
- Performance on long, ambiguous, or changing tasks.
Microsoft customers may prefer Microsoft 365 Copilot for integrated workplace workflows, or Azure AI Foundry and Azure OpenAI for cloud deployment, governance, and integration. Developers can evaluate the OpenAI API, while enterprises comparing major providers may also consider Anthropic Claude for Enterprise.
Prices, model availability, plans, and enterprise terms change frequently. Buyers should verify current details on the vendors’ official pages rather than rely on an AGI announcement—or on an old price quote.
The bottom line on Microsoft and OpenAI
“Microsoft no longer believes OpenAI is capable of achieving AGI” is a provocative interpretation, not an established Microsoft statement. Nadella’s documented position was that self-declared AGI milestones amount to “nonsensical benchmark hacking” when they substitute narrow scores for measurable economic and workplace results.
Later reporting added a contractual dispute: Microsoft reportedly did not expect OpenAI to meet the relevant AGI condition before 2030, while OpenAI considered whether an earlier declaration was possible. The evidence therefore shows a fight over definitions, measurement, timing, and control—not proof that Microsoft believes OpenAI can never achieve AGI.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
