MAI-Thinking-1
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Microsoft
- Organisation type
- Industry
- Country
- United States of America
- Published
- 2 June 2026
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation, Question answering
- Numerical format
- BF16
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 962B
- Training data
- 33,550,000,000,000 tokens
- Epochs
- 1.03
34.7B active, 962B total from Table 1
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- Training compute
- 7 × 10²⁴ FLOP
6 * 34.7e9 parameters * 33.55e12 tokens = 6.98511e24 FLOP
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA GB200
- Chips used
- 8,192
- Power draw
- 19.1 MW
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- API access
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- MAI-Thinking-1: Building a Hill-Climbing Machine
- Last updated
- 21 July 2026
What the numbers mean
Background
MAI-Thinking-1 was published by Microsoft, in United States of America, in June 2026. industry is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling/generation, Question answering.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
Producing it required around 7 × 10²⁴ FLOP of arithmetic, on NVIDIA GB200, which is a statement about the training budget rather than about inference.
It was trained on about 33,550,000,000,000 tokens of text.
Answers
MAI-Thinking-1 — common questions
When was MAI-Thinking-1 released?
MAI-Thinking-1 was published in June 2026.
What is MAI-Thinking-1 used for?
MAI-Thinking-1 works in Language, and is recorded as handling language modeling/generation, Question answering. These are the areas it was designed around; they describe intent rather than a hard boundary.
How much compute was used to train MAI-Thinking-1?
Around 7 × 10²⁴ FLOP, on NVIDIA GB200. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
What GPU do I need to run MAI-Thinking-1?
None. MAI-Thinking-1 is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is MAI-Thinking-1 open source?
No. MAI-Thinking-1 has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does MAI-Thinking-1 have?
MAI-Thinking-1 has 962B parameters. 34.7B active, 962B total from Table 1. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created MAI-Thinking-1?
MAI-Thinking-1 was published by Microsoft, based in United States of America, categorised as industry.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.