Voyage AI - API - verified
Voyage Multimodal 3.5 embeddings
Voyage Multimodal 3.5 is a current embedding model from Voyage AI, called by API as voyage-multimodal-3.5. It returns 1,024-dimension vectors by default and accepts up to 32,000 input tokens, for text, image and video input. The first-party list price is $0.12 per 1M input tokens.
CurrentModel id: voyage-multimodal-3.5
- Default dims
- 1,024
- Max input
- 32,000 tok
- Price / 1M
- $0.12
- Inputs
- Text, Image, Video
Dimensions
Flexible output size- 2,048
- 1,024default
- 512
- 256
Default output: 1,024 dimensions.
Listed sizes: 2,048, 1,024, 512 and 256.
Voyage AI documents shorter output vectors for this model (Matryoshka-style), so you can store smaller embeddings by asking for fewer dimensions instead of re-embedding with another model.
Pricing
- Per 1M input tokens
- $0.12
- Batch, per 1M
- Not stated
$0.12 per 1M text tokens plus $0.60 per billion pixels; first 200M text tokens and 150B pixels free.
Source: docs.voyageai.com/docs/pricing
Usage
Copied verbatim from the page linked below. Placeholders such as project ids and API keys are the source's own.
import voyageai
from voyageai.video_utils import Video
import PIL
vo = voyageai.Client()
# This will automatically use the environment variable VOYAGE_API_KEY.
# Alternatively, you can use vo = voyageai.Client(api_key="<your secret key>")
# Example input containing a text string, Image object, and Video object
inputs = [
["This is a banana.", PIL.Image.open("banana.jpg"), Video.from_path("banana.mp4", model="voyage-multimodal-3.5")]
]
# Vectorize inputs
result = vo.multimodal_embed(inputs, model="voyage-multimodal-3.5")
print(result.embeddings)Worth knowing
Vectorizes interleaved text, images and video through a single backbone for mixed-modality retrieval over screenshots, slides, tables and figures.
Release date not stated in the sources. Multilingual: not stated.
FAQ
How many dimensions does Voyage Multimodal 3.5 output?
Default output: 1,024 dimensions. Listed sizes: 2,048, 1,024, 512 and 256. Voyage AI documents shorter output vectors for this model (Matryoshka-style), so you can store smaller embeddings by asking for fewer dimensions instead of re-embedding with another model.
What is the max input length of Voyage Multimodal 3.5?
32,000 tokens per input, per Voyage AI's documentation. Longer text has to be chunked before you embed it.
How much does Voyage Multimodal 3.5 cost?
The first-party list price is $0.12 per 1M input tokens. $0.12 per 1M text tokens plus $0.60 per billion pixels; first 200M text tokens and 150B pixels free. Source: https://docs.voyageai.com/docs/pricing.
What can Voyage Multimodal 3.5 embed?
Text, image and video input, per the provider.
Sources
Last verified from the pages below.
- Voyage multimodal embeddings docs - docs.voyageai.com
- Voyage pricing - docs.voyageai.com
More Voyage AI embedding models
Default dimensions, max input tokens and list price per 1M tokens.
- Voyage 4 Large1,024 dims - 32,000 tokens - $0.12
- Voyage 41,024 dims - 32,000 tokens - $0.06
- Voyage 4 Lite1,024 dims - 32,000 tokens - $0.02
- Voyage Code 41,024 dims - 32,000 tokens - $0.12
- Voyage Context 41,024 dims - 32,000 tokens - $0.12
- Voyage Finance 21,024 dims - 32,000 tokens - $0.12
- Voyage Law 21,024 dims - 16,000 tokens - $0.12
- Voyage 4 Nano1,024 dims - 32,000 tokens - Self-hosted
- Voyage 3 LargeLegacy1,024 dims - 32,000 tokens - $0.18
- Voyage 3.5Legacy1,024 dims - 32,000 tokens - $0.06
- Voyage 3.5 LiteLegacy1,024 dims - 32,000 tokens - $0.02
- Voyage Code 3Legacy1,024 dims - 32,000 tokens - $0.18
- Voyage Context 3Legacy1,024 dims - 32,000 tokens - $0.18
- Voyage Multimodal 3Legacy1,024 dims - 32,000 tokens - $0.12
- Voyage 3Legacy1,024 dims - 32,000 tokens - $0.06
- Voyage 3 LiteLegacy512 dims - 32,000 tokens - $0.02
- Voyage Multilingual 2Legacy1,024 dims - 32,000 tokens - $0.12
- Voyage Large 2 InstructLegacy1,024 dims - 16,000 tokens - $0.12
- Voyage Large 2Legacy1,536 dims - 16,000 tokens - $0.12
- Voyage 2Legacy1,024 dims - 4,000 tokens - $0.10
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