Microsoft says its own Maia 300 chip will run most of its AI inference from 2027
Training stays on Nvidia and AMD for now. Answering Copilot queries is moving onto Microsoft's own silicon.
글 The desk, News · · 1분 읽기
태그: microsoft · chips · maia · inference
이 기사는 아직 한국어로 없습니다. 영어를 읽습니다.
- 이 소식
- Training stays on Nvidia and AMD for now.
- 왜 중요한가
- Answering Copilot queries is moving onto Microsoft's own silicon.
- 확인된 것
- The photograph is generated for this story.
이름을 밝힌 출처에 묶여 있다. 검증됨으로 표시하지 않았다. Microsoft Azure blog
The news
Microsoft announced Maia 300, built on TSMC's N2P process with eight HBM4 memory stacks and a 950-watt power budget. Cloud chief Scott Guthrie said Microsoft will scale the Maia family to multi-gigawatt deployments starting in 2027 and make it the primary inference system for Microsoft's own products.
Why it matters
Inference is where most AI compute spending is heading. A hyperscaler saying it will serve most of it on its own chips is a direct threat to Nvidia's share of that budget.
The details
Microsoft claims 40 percent more tokens per megawatt than leading GPU systems and up to seven times the per-rack throughput of Maia 200. Both figures are vendor-reported, and the comparison GPU is not named. A rack holds 96 chips in a 167-kilowatt envelope.
CNBC reported that Microsoft will keep using Nvidia and AMD hardware to train models.
What we could not check
- The GPU used for Microsoft's efficiency comparison was not named.
- No independent benchmark of Maia 300 exists yet.
출처
The photograph is generated for this story. It does not show the people named in it.