Learn about supported models

For mobile and web apps, the Vertex AI in Firebase SDKs let you interact with the supported Gemini models directly from your app.

Gemini models are considered multimodal because they're capable of processing and even generating multiple modalities, including text, code, PDFs, images, video, and audio.

The following table is a brief overview of supported models for Vertex AI in Firebase and their latest stable model names. This table also lists preview and experimental models that are available for prototyping use cases.

Model Input Output Description
Gemini stable models
Gemini 2.0 Flash
gemini-2.0-flash-001 		text, code, PDFs, images, video, audio text, code, JSON
(images & audio coming soon!)		 Provides next generation features and speed for a diverse variety of tasks
(multimodal generation coming soon!)
Gemini 1.5 Pro
gemini-1.5-pro-002		 text, code, PDFs, images, video, audio text, code, JSON Supports complex reasoning tasks requiring more intelligence; 2M long context
Gemini 1.5 Flash
gemini-1.5-flash-002		 text, code, PDFs, images, video, audio text, code, JSON Offers fast and versatile performance across a diverse variety of tasks
Gemini preview and experimental models (recommended for prototyping use cases only)
Gemini 2.0 Pro
gemini-2.0-pro-exp-02-05 		text, code, PDFs, images, video, audio text, code, JSON Offers the strongest model quality, especially for code and world knowledge; 2M long context
Gemini 2.0 Flash Lite
gemini-2.0-flash-lite-preview-02-05 		text, code, PDFs, images, video, audio text, code, JSON Provides cost effective and low latency performance; supports high throughput
Gemini 2.0 Flash Thinking
gemini-2.0-flash-thinking-exp-01-21 		text, code, PDFs, images text, code, JSON Offers stronger reasoning capabilities and includes the thinking process in responses


The remainder of this page provides detailed information about the models supported by Vertex AI in Firebase:

  • Compare models:

    • Supported input and output
    • High-level comparison of the supported capabilities
    • Specifications and limitations, for example max input tokens or max length of input video

  • Description of how models are versioned, specifically their stable, auto-updated, and preview versions

  • Lists of available model names to include in your code during initialization

  • Lists of supported languages for the models

At the bottom of this page, you can view detailed information about older models.


Compare models

Each model has different capabilities to support various use cases. Note that each of tables in this section describe each model when used with Vertex AI in Firebase. Each model might have additional capabilities that aren't available when using our SDKs.

If you can't find the information you're looking for in the following sub-sections, you can find even more information about the Gemini models in the Google Cloud documentation.

Supported input and output

These are the supported input and output types when using each model with Vertex AI in Firebase:

Gemini
2.0 Pro 		Gemini
2.0 Flash 		Gemini
2.0 Flash
Lite 		Gemini
2.0 Flash
Thinking 		Gemini
1.5 Pro 		Gemini
1.5 Flash
Input types
Text
Code
Documents
(PDFs or plain-text)
Images
Video
Audio
Audio (streaming) coming soon!
Output types
Text
Code
Structured output
(like JSON)
Images coming soon!
Audio coming soon!
Audio (streaming) coming soon!

To learn about supported file types, see Supported input files and requirements for the Vertex AI Gemini API.

Supported capabilities and features

These are the supported capabilities and features when using each model with Vertex AI in Firebase:

Gemini
2.0 Pro 		Gemini
2.0 Flash 		Gemini
2.0 Flash
Lite 		Gemini
2.0 Flash
Thinking 		Gemini
1.5 Pro 		Gemini
1.5 Flash
Generate text from text or multimodal inputs
Generate images coming soon!
Generate audio coming soon!
Generate structured output
(like JSON)
Analyze documents
(PDFs or plain-text)
Analyze images (vision)
Analyze video (vision)
Analyze audio
Multi-turn chat
Function calling (tools)
Count tokens and billable characters
System instructions
Multimodal Live API
(bidirectional streaming) 		coming soon!

Specifications and limitations

These are the specifications and limitations when using each model with Vertex AI in Firebase:

Property Gemini
2.0 Pro 		Gemini
2.0 Flash 		Gemini
2.0 Flash
Lite 		Gemini
2.0 Flash
Thinking 		Gemini
1.5 Pro 		Gemini
1.5 Flash
Context window *
Total token limit
(combined input+output) 		2,097,152 tokens 1,048,576 tokens 1,048,576 tokens 1,048,576 tokens 2,097,152 tokens 1,048,576 tokens
Output token limit * 8,192 tokens 8,192 tokens 8,192 tokens 8,192 tokens 8,192 tokens 8,192 tokens
Knowledge cutoff date June 2024 June 2024 June 2024 June 2024 May 2024 May 2024
PDFs (per request)
Max number
of input PDF files **		 3,000 files 3,000 files 3,000 files 3,000 files 3,000 files 3,000 files
Max number
of pages per input PDF file **		 1,000 pages 1,000 pages 1,000 pages 1,000 pages 1,000 pages 1,000 pages
Max size
per input PDF file		 50 MB 50 MB 50 MB 50 MB 50 MB 50 MB
Images (per request)
Max number
of input images		 3,000 images 3,000 images 3,000 images 3,000 images 3,000 images 3,000 images
Max number
of output images		 --- coming soon! --- --- --- ---
Max size
per input base64-encoded image		 7 MB 7 MB 7 MB 7 MB 7 MB 7 MB
Video (per request)
Max number
of input video files		 10 files 10 files 10 files --- 10 files 10 files
Max length
of all input video
(frames only)		 ~60 minutes ~60 minutes ~60 minutes --- ~60 minutes ~60 minutes
Max length
of all input video
(frames+audio)		 ~45 minutes ~45 minutes ~45 minutes --- ~45 minutes ~45 minutes
Audio (per request)
Max number
of input audio files		 1 file 1 file 1 file --- 1 file 1 file
Max number
of output audio files		 --- coming soon! --- --- --- ---
Max length
of all input audio		 ~8.4 hours ~8.4 hours ~8.4 hours --- ~8.4 hours ~8.4 hours
Max length
of all output audio		 --- coming soon! --- --- --- ---

* For all models, a token is equivalent to about 4 characters, so 100 tokens are about 60-80 English words. For Gemini models, you can determine the total count of tokens in your requests using countTokens.

** PDFs are treated as images, so a single page of a PDF is treated as one image. The number of pages allowed in a request is limited to the number of images the model can support.

Find additional detailed information


Model versioning and naming patterns

Models are offered in stable, preview, and experimental versions. For convenience, aliases without explicit version values are supported.

To find specific model names to use in your code, see the "available model names" section later on this page.

Version type Description Model name pattern
Stable Stable versions are considered Generally Available.

Model names of stable versions are appended with a specific three-digit version number

Example: gemini-2.0-flash-001
Auto-updated stable alias Auto-updated stable aliases always point to the latest stable version of that model. If a new stable version is released, the auto-updated alias automatically starts pointing to that new stable version.

Model names of aliases have no appendage

Example: gemini-2.0-flash

Preview Preview versions have new capabilities and are considered not stable.

Preview versions always point to the latest preview version of that model. If a new preview version is released, any existing preview version automatically starts pointing to that new preview version.

Model names of preview versions are appended with -preview along with the model's initial release date (-MMDD)

Example: gemini-2.0-flash-lite-preview-02-05
(released on February 5, 2025)

Experimental Experimental versions have new capabilities and are considered not stable and don't follow Google's standard model lifecycle plan and versioning scheme.

Learn more about experimental models.

Model names of experimental versions are appended with -exp along with the model's initial release date (-MMDD)

Example: gemini-2.0-pro-exp-02-05
(released on February 5, 2025)

Learn more about the available model versions and their lifecycle (Gemini) in the Google Cloud documentation.


Available model names

Model names are the explicit values that you include in your code during initialization of the generative model (which is a required step to call the Gemini API).

You can use the publishers.models.list endpoint to list all available model names. Note that this returned list will include all models that Vertex AI supports, but Vertex AI in Firebase only supports the Gemini models described on this page. Also note that auto-updated aliases (for example, gemini-2.0-flash) aren't listed because they're a convenience alias for the base model.

Gemini model names

For initialization examples for your language, see the getting started guide.

Gemini 2.0 Pro model names

Model name Description Release stage Initial release date Discontinuation date
Stable versions
No stable versions available --- --- --- ---
Auto-updated stable alias
No auto-updated stable alias available --- --- --- ---
Preview versions
No preview versions available --- --- --- ---
Experimental versions
gemini-2.0-pro-exp-02-05 Experimental version of Gemini 2.0 Pro Experimental 2025-02-05 To be determined

Gemini 2.0 Flash model names

Model name Description Release stage Initial release date Discontinuation date
Stable versions
gemini-2.0-flash-001 Latest stable version of Gemini 2.0 Flash General Availability 2025-02-05 To be determined
Auto-updated stable alias
gemini-2.0-flash Points to the latest stable version of 2.0 Flash
(currently gemini-2.0-flash-001) 		General Availability 2025-02-10 ---
Preview versions
No preview versions available --- --- --- ---
Experimental versions
No experimental versions available --- --- --- ---

Gemini 2.0 Flash Lite model names

Model name Description Release stage Initial release date Discontinuation date
Stable versions
No stable versions available --- --- --- ---
Auto-updated stable alias
No auto-updated stable alias available --- --- --- ---
Preview versions
gemini-2.0-flash-lite-preview-02-05 Preview version of Gemini 2.0 Flash Lite Preview 2025-02-05 To be determined
Experimental versions
No experimental versions available --- --- --- ---

Gemini 2.0 Flash Thinking model names

Model name Description Release stage Initial release date Discontinuation date
Stable versions
No stable versions available --- --- --- ---
Auto-updated stable alias
No auto-updated stable alias available --- --- --- ---
Preview versions
No preview versions available --- --- --- ---
Experimental versions
gemini-2.0-flash-thinking-exp-01-21 Experimental version of Gemini 2.0 Flash Thinking Experimental 2025-01-21 To be determined

Gemini 1.5 Pro model names

Model name Description Release stage Initial release date Discontinuation date
Stable versions
gemini-1.5-pro-002 Latest stable version of Gemini 1.5 Pro General Availability 2024-09-24 No earlier than 2025-09-24
gemini-1.5-pro-001 Initial stable version of Gemini 1.5 Pro General Availability 2024-05-24 No earlier than 2025-05-24
Auto-updated stable alias
gemini-1.5-pro Points to the latest stable version of 1.5 Pro
(currently gemini-1.5-pro-002) 		General Availability 2024-09-24 ---
Preview versions
No preview versions available --- --- --- ---
Experimental versions
No experimental versions available --- --- --- ---

Gemini 1.5 Flash model names

Model name Description Release stage Initial release date Discontinuation date
Stable versions
gemini-1.5-flash-002 Latest stable version of Gemini 1.5 Flash General Availability 2024-09-24 No earlier than 2025-09-24
gemini-1.5-flash-001 Initial stable version of Gemini 1.5 Flash General Availability 2024-05-24 No earlier than 2025-05-24
Auto-updated stable alias
gemini-1.5-flash Points to the latest stable version of 1.5 Flash
(currently gemini-1.5-flash-002) 		General Availability 2024-09-24 ---
Preview versions
No preview versions available --- --- --- ---
Experimental versions
No experimental versions available --- --- --- ---


Supported languages

Gemini

  • All the Gemini models can understand and respond in the following languages:

    Arabic (ar), Bengali (bn), Bulgarian (bg), Chinese simplified and traditional (zh), Croatian (hr), Czech (cs), Danish (da), Dutch (nl), English (en), Estonian (et), Finnish (fi), French (fr), German (de), Greek (el), Hebrew (iw), Hindi (hi), Hungarian (hu), Indonesian (id), Italian (it), Japanese (ja), Korean (ko), Latvian (lv), Lithuanian (lt), Norwegian (no), Polish (pl), Portuguese (pt), Romanian (ro), Russian (ru), Serbian (sr), Slovak (sk), Slovenian (sl), Spanish (es), Swahili (sw), Swedish (sv), Thai (th), Turkish (tr), Ukrainian (uk), Vietnamese (vi)

  • Gemini 1.5 Pro and Gemini 1.5 Flash models can understand and respond in the following additional languages:

    Afrikaans (af), Amharic (am), Assamese (as), Azerbaijani (az), Belarusian (be), Bosnian (bs), Catalan (ca), Cebuano (ceb), Corsican (co), Welsh (cy), Dhivehi (dv), Esperanto (eo), Basque (eu), Persian (fa), Filipino (Tagalog) (fil), Frisian (fy), Irish (ga), Scots Gaelic (gd), Galician (gl), Gujarati (gu), Hausa (ha), Hawaiian (haw), Hmong (hmn), Haitian Creole (ht), Armenian (hy), Igbo (ig), Icelandic (is), Javanese (jv), Georgian (ka), Kazakh (kk), Khmer (km), Kannada (kn), Krio (kri), Kurdish (ku), Kyrgyz (ky), Latin (la), Luxembourgish (lb), Lao (lo), Malagasy (mg), Maori (mi), Macedonian (mk), Malayalam (ml), Mongolian (mn), Meiteilon (Manipuri) (mni-Mtei), Marathi (mr), Malay (ms), Maltese (mt), Myanmar (Burmese) (my), Nepali (ne), Nyanja (Chichewa) (ny), Odia (Oriya) (or), Punjabi (pa), Pashto (ps), Sindhi (sd), Sinhala (Sinhalese) (si), Samoan (sm), Shona (sn), Somali (so), Albanian (sq), Sesotho (st), Sundanese (su), Tamil (ta), Telugu (te), Tajik (tg), Uyghur (ug), Urdu (ur), Uzbek (uz), Xhosa (xh), Yiddish (yi), Yoruba (yo), Zulu (zu)


Information about older models

Vertex AI in Firebase supports all Gemini models, including older models like Gemini 1.0 Pro and Gemini 1.0 Pro Vision. However, we strongly recommend using a newer model with our SDKs. These older Gemini models are approaching their discontinuation date and don't offer all the capabilities of the newer models.


Next steps

Try out the capabilities of the Gemini API