Microsoft MAI-1 (2024 unreleased)
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
- 6 May 2024
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling, Language modeling/generation
- Approach
- Supervised
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
- 500B
- Training data
- tokens
500B
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
- 1.6 × 10²² FLOP
989400000000000 FLOP/GPU/sec * 15000 GPU-hours * 3600 sec / hour * 0.3 [assumed utilization] = 1.602828e+22 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 H100 SXM5 80GB
- Chip-hours
- 15,000
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
- Hosted access (no API)
- 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
- Meet MAI-1: Microsoft Readies New AI Model to Compete With Google, OpenAI
- Last updated
- 20 March 2026
What the numbers mean
Background
Microsoft MAI-1 (2024 unreleased) was published by Microsoft, in the country recorded as United States of America, during May 2024. The publishing organisation is categorised as industry.
It works in the domain of Language, and is recorded as performing the task of language modeling, Language modeling/generation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Training and provenance
The training run consumed about 1.6 × 10²² FLOP, on hardware recorded as NVIDIA H100 SXM5 80GB. That figure measures what producing the model cost, and has no bearing on how fast it answers.
Answers
Microsoft MAI-1 (2024 unreleased) — common questions
Microsoft MAI-1 (2024 unreleased)— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling, Language modeling/generation. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
Microsoft MAI-1 (2024 unreleased)— how much compute was used to train it?
Training consumed around 1.6 × 10²² FLOP, on hardware recorded as NVIDIA H100 SXM5 80GB. 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.
Microsoft MAI-1 (2024 unreleased)— what GPU do I need to run it?
None. This 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.
Microsoft MAI-1 (2024 unreleased)— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Microsoft MAI-1 (2024 unreleased)— how many parameters does it have?
It has a parameter count of 500B. 500B. 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.
Microsoft MAI-1 (2024 unreleased)— who created it?
It was published by Microsoft, based in United States of America, an organisation categorised as industry.
Microsoft MAI-1 (2024 unreleased)— when was it released?
It was published in May 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.