Sparrow
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
- DeepMind
- Organisation type
- Industry
- Country
- United Kingdom of Great Britain and Northern Ireland
- Published
- 28 September 2022
- Authors
- Amelia Glaese, Nat McAleese, Maja Trębacz, John Aslanides, Vlad Firoiu, Timo Ewalds, Maribeth Rauh, Laura Weidinger, Martin Chadwick, Phoebe Thacker, Lucy Campbell-Gillingham, Jonathan Uesato, Po-Sen Huang, Ramona Comanescu, Fan Yang, Abigail See, Sumanth Dathathri, Rory Greig, Charlie Chen, Doug Fritz, Jaume Sanchez Elias, Richard Green, Soňa Mokrá, Nicholas Fernando, Boxi Wu, Rachel Foley, Susan…
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Chat, Language modeling/generation, Question answering
- Base model
- Chinchilla
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
- 70B
- Training data
- tokens
70B
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
- Unreleased
- 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
- Record confidence
- Confident
- Citations
- 665
Sources
Where this record came from and when it was last checked.
- Reference
- Improving alignment of dialogue agents via targeted human judgements
- Last updated
- 25 May 2026
What the numbers mean
Background
Sparrow was published by DeepMind, in United Kingdom of Great Britain and Northern Ireland, in September 2022. industry is the category the publisher falls under.
It works in Language, and is recorded as doing chat, Language modeling/generation, Question answering.
It builds on Chinchilla, which is why it shares that model's general shape and size.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Sparrow — common questions
Who created Sparrow?
Sparrow was published by DeepMind, based in United Kingdom of Great Britain and Northern Ireland, categorised as industry.
When was Sparrow released?
Sparrow was published in September 2022. 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 Sparrow used for?
Sparrow works in Language, and is recorded as handling chat, Language modeling/generation, Question answering. 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.
What GPU do I need to run Sparrow?
None. Sparrow 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 Sparrow open source?
No. Sparrow has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Sparrow have?
Sparrow has 70B parameters. 70B. 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.
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.