This page gives you information about legacy generative AI models on Vertex AI. The models in a legacy model family are no longer updated with new stable versions. After all stable versions of a legacy model reach their discontinuation dates, the model family is no longer supported.
PaLM API models
The following table summarizes PaLM API legacy models:
Model name | Description | Model properties | Tuning support |
---|---|---|---|
PaLM 2 for Text ( text-bison ) |
Fine-tuned to follow natural language instructions and is suitable for a variety of language tasks, such as classification, summarization, and extraction. | Maximum input tokens: 8192 Maximum output tokens: 1024 Training data: Up to Feb 2023 |
Supervised: Yes RLHF: Yes (Preview) Distillation: No |
PaLM 2 for Text (text-unicorn ) |
The most advanced text model in the PaLM family of models for use with complex natural language tasks. | Maximum input tokens: 8192 Maximum output tokens: 1024 Training data: Up to Feb 2023 |
Supervised: No RLHF: No Distillation: Yes (Preview) |
PaLM 2 for Text 32k ( text-bison-32k ) |
Fine-tuned to follow natural language instructions and is suitable for a variety of language tasks. | Max tokens (input + output): 32,768 Max output tokens: 8,192 Training data: Up to Aug 2023 |
Supervised: Yes RLHF: No Distillation: No |
PaLM 2 for Chat ( chat-bison ) |
Fine-tuned for multi-turn conversation use cases. | Maximum input tokens: 8192 Maximum output tokens: 2048 Training data: Up to Feb 2023 Maximum turns : 2500 |
Supervised: Yes RLHF: No Distillation: No |
PaLM 2 for Chat 32k ( chat-bison-32k ) |
Fine-tuned for multi-turn conversation use cases. | Max tokens (input + output): 32,768 Max output tokens: 8,192 Training data: Up to Aug 2023 Max turns : 2500 |
Supervised: Yes RLHF: No Distillation: No |
Codey APIs models
The following table summarizes Codey APIs legacy models. Note that
code-gecko
code completion model is not a legacy model.
Model name | Description | Model properties | Tuning support |
---|---|---|---|
Codey for Code Generation ( code-bison ) |
A model fine-tuned to generate code based on a natural language description of the desired code. For example, it can generate a unit test for a function. | Maximum input tokens: 6144 Maximum output tokens: 1024 |
Supervised: Yes RLHF: No Distillation: No |
Codey for Code Generation 32k ( code-bison-32k ) |
A model fine-tuned to generate code based on a natural language description of the desired code. For example, it can generate a unit test for a function. | Max tokens (input + output): 32,768 Max output tokens: 8,192 |
Supervised: Yes RLHF: No Distillation: No |
Codey for Code Chat ( codechat-bison ) |
A model fine-tuned for chatbot conversations that help with code-related questions. | Maximum input tokens: 6144 Maximum output tokens: 1024 |
Supervised: Yes RLHF: No Distillation: No |
Codey for Code Chat 32k ( codechat-bison-32k ) |
A model fine-tuned for chatbot conversations that help with code-related questions. | Max tokens (input + output): 32,768 Max output tokens: 8,192 |
Supervised: Yes RLHF: No Distillation: No |
Language support
Vertex AI PaLM API and Codey APIs legacy models support 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
)
Legacy model discontinuation date
The following table shows the discontinuation date of legacy models:
chat-bison model | Release date | Discontinuation date |
---|---|---|
chat-bison@002 | December 6, 2023 | April 9, 2025 |
chat-bison-32k model | Release date | Discontinuation date |
---|---|---|
chat-bison-32k@002 | December 4, 2023 | April 9, 2025 |
code-bison model | Release date | Discontinuation date |
---|---|---|
code-bison@002 | December 6, 2023 | April 9, 2025 |
code-bison-32k model | Release date | Discontinuation date |
---|---|---|
code-bison-32k@002 | December 4, 2023 | April 9, 2025 |
codechat-bison model | Release date | Discontinuation date |
---|---|---|
codechat-bison@002 | December 6, 2023 | April 9, 2025 |
codechat-bison-32k model | Release date | Discontinuation date |
---|---|---|
codechat-bison-32k@002 | December 4, 2023 | April 9, 2025 |
text-bison model | Release date | Discontinuation date |
---|---|---|
text-bison@002 | December 6, 2023 | April 9, 2025 |
text-bison-32k model | Release date | Discontinuation date |
---|---|---|
text-bison-32k@002 | December 4, 2023 | April 9, 2025 |
text-unicorn model | Release date | Discontinuation date |
---|---|---|
text-unicorn@001 | November 30, 2023 | April 9, 2025 |
Legacy models that support Provisioned Throughput
This table shows legacy models that support Provisioned Throughput, which is measured in characters per second, minimum purchase increments, and burndown rates.
Model | Throughput per GSU | Minimum GSU purchase increment | Burndown rates |
---|---|---|---|
text-bison , chat-bison ,
code-bison , codechat-bison |
4,000 | 1 | 1 input char = 1 char 1 output char = 2 chars |
text-unicorn |
400 | 1 | 1 input char = 1 char 1 output char = 3 chars |