Inflection-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
- Inflection AI
- Organisation type
- Industry
- Country
- United States of America
- Published
- 23 June 2023
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
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.
- Training data
- tokens
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 × 10²⁴ FLOP
- How it was established
- Comparison with other models
<= 2.5e24 They define two "compute classes", one for models with more compute than PaLM 540B, i.e. GPT-4 and PaLM 2, and one for models with as much compute or less, i.e. GPT-3.5, Chinchilla, LLaMA, and Inflection-1. PaLM 540B required 2.5e24 FLOP to train (confirmed by Google)
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
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.
- Foundation model
- Yes
- Likely above 10²³ FLOP
- Yes
- Record confidence
- Speculative
Sources
Where this record came from and when it was last checked.
- Reference
- Inflection-1 technical memo
- Last updated
- 28 November 2025
What the numbers mean
Background
Inflection-1 was published by Inflection AI, in United States of America, in June 2023. The organisation is categorised as industry.
It works in Language, and is recorded as doing language modeling.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
The training run consumed about 1 × 10²⁴ FLOP, on NVIDIA H100 SXM5 80GB. That figure describes the cost of creating it and has no bearing on how quickly it generates text.
Answers
Inflection-1 — common questions
How many parameters does Inflection-1 have?
No parameter count has been published for Inflection-1, which is why no memory or speed figure appears on this page.
Who created Inflection-1?
Inflection-1 was published by Inflection AI, based in United States of America, categorised as industry.
When was Inflection-1 released?
Inflection-1 was published in June 2023. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Inflection-1 used for?
Inflection-1 works in Language, and is recorded as handling language modeling. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
How much compute was used to train Inflection-1?
Around 1 × 10²⁴ FLOP, on 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.
What GPU do I need to run Inflection-1?
None. Inflection-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 Inflection-1 open source?
No. Inflection-1 has not had its weights published, so it exists only as a service controlled by its owner.
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.