Gemini 1.5 Flash
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
- Google DeepMind
- Organisation type
- Industry
- Country
- United States of America
- Published
- 10 May 2024
- Authors
- Gemini Team
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Multimodal, Language, Vision, Audio
- Task
- Chat, Image captioning, Visual question answering, Translation, Language modeling/generation, Question answering, Speech recognition (ASR)
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
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
- Google TPU v4
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
API access: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
- Last updated
- 11 February 2026
What the numbers mean
Background
Gemini 1.5 Flash was published by Google DeepMind, in United States of America, in May 2024. It comes out of industry.
It works in Multimodal, Language, Vision, Audio, and is recorded as doing chat, Image captioning, Visual question answering, Translation, Language modeling/generation, Question answering, Speech recognition (ASR).
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Gemini 1.5 Flash — common questions
How many parameters does Gemini 1.5 Flash have?
No parameter count has been published for Gemini 1.5 Flash, which is why no memory or speed figure appears on this page.
Who created Gemini 1.5 Flash?
Gemini 1.5 Flash was published by Google DeepMind, based in United States of America, categorised as industry.
When was Gemini 1.5 Flash released?
Gemini 1.5 Flash 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.
What is Gemini 1.5 Flash used for?
Gemini 1.5 Flash works in Multimodal, Language, Vision, Audio, and is recorded as handling chat, Image captioning, Visual question answering, Translation, Language modeling/generation, Question answering, Speech recognition (ASR). These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Gemini 1.5 Flash?
None. Gemini 1.5 Flash 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 Gemini 1.5 Flash open source?
No. Gemini 1.5 Flash 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.