SWE-1.5
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
- Cognition
- Organisation type
- Industry
- Country
- United States of America
- Published
- 29 October 2025
- Authors
- Jacob Teo, Nikhil Jha, Connor Fogarty, Gary Chang, Theodor Marcu, Edison Zhang, Albert Tam, Sean Sullivan, Swyx, Silas Alberti
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Code generation
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
- 300B
- Training data
- tokens
"hundreds of billions of parameters" Assuming ~300B with "Likely" confidence
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
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
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- Introducing SWE-1.5: Our Fast Agent Model
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
SWE-1.5 was published by Cognition, in the country recorded as United States of America, during October 2025. The category the publisher falls under is industry.
It works in the domain of Language, and is recorded as performing the task of code generation.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Answers
SWE-1.5 — common questions
SWE-1.5— how many parameters does it have?
It has a parameter count of 300B. "hundreds of billions of parameters" Assuming ~300B with "Likely" confidence. 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.
SWE-1.5— who created it?
It was published by Cognition, based in United States of America, an organisation categorised as industry.
SWE-1.5— when was it released?
It was published in October 2025.
SWE-1.5— what is it used for?
It works in the domain of Language, and is recorded as handling the task of code generation. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
SWE-1.5— 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.
SWE-1.5— is it open source?
No. Its weights have not been 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.