---
title: "multimodalembedding - Model Details & Comparison"
description: "multimodalembedding from Google Vertex AI: capabilities, context limits, pricing, and side-by-side comparisons with alternative models."
url: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/vertex_ai/multimodalembedding"
markdown: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/vertex_ai/multimodalembedding.md"
---

# multimodalembedding - Model Details & Comparison

> multimodalembedding from Google Vertex AI: capabilities, context limits, pricing, and side-by-side comparisons with alternative models.

## Important Links

- [View MCP Gateway](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources/mcp-gateway.md)
- [Features](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/#features)
- [Enterprise](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/enterprise)
- [Pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/pricing.md)
- [Docs](https://docs.getbifrost.ai)
- [GitHub](https://github.com/maximhq/bifrost)
- [Book a Demo](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/book-a-demo)

## About multimodalembedding

multimodalembedding is an embedding model from Vertex AI, one of 10 embedding models they offer. It is priced at $0.80 per 1M input tokens and $0.0000 per 1M output tokens, ranking 140 out of 145 embedding models by cost and cheaper than 3% of models in this category. It accepts up to 2K input tokens.

## Specifications

- **Google Vertex AI Provider.**
- **Embedding Mode.**
- **2,048 Max Input Tokens.**
- **2,048 Max Tokens.**
- **$0.80 / 1M tokens Input Price.**
- **$0.0000 / 1M tokens Output Price.**

## multimodalembedding Pricing Overview

At $0.80 per 1M input tokens and $0.0000 per 1M output tokens, multimodalembedding ranks 140 out of 145 embedding models by input cost. It is more expensive compared to the median of $0.10 for embedding models, and is cheaper than 3% of models in this category.

## Models to Compare

Alternatives to multimodalembedding with comparable capabilities.

| Model | Provider | Input $/1M | Output $/1M |
| --- | --- | --- | --- |
| amazon.titan-embed-image-v1 | AWS Bedrock | $0.80 | $0.0000 |
| amazon.nova-2-multimodal-embeddings-v1:0 | AWS Bedrock | $0.14 | $0.0000 |
| amazon.titan-embed-text-v1 | AWS Bedrock | $0.10 | $0.0000 |
| amazon.titan-embed-g1-text-02 | AWS Bedrock | $0.10 | $0.0000 |
| amazon.titan-embed-text-v2:0 | AWS Bedrock | $0.02 | $0.0000 |

- [Compare amazon.titan-embed-image-v1](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/amazon.titan-embed-image-v1.md)
- [Compare amazon.nova-2-multimodal-embeddings-v1:0](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/amazon.nova-2-multimodal-embeddings-v1-0.md)
- [Compare amazon.titan-embed-text-v1](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/amazon.titan-embed-text-v1.md)
- [Compare amazon.titan-embed-g1-text-02](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/amazon.titan-embed-g1-text-02.md)
- [Compare amazon.titan-embed-text-v2:0](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/amazon.titan-embed-text-v2-0.md)

## Related Resources

- [Calculate multimodalembedding costs](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/vertex_ai/model/multimodalembedding.md)
- [All Vertex AI pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/vertex_ai.md)

## FAQ

### Is multimodalembedding cheaper than amazon.titan-embed-image-v1?

No. multimodalembedding costs $0.80 per 1M input tokens while amazon.titan-embed-image-v1 costs $0.80 per 1M input tokens, making amazon.titan-embed-image-v1 0% more affordable for input. However, multimodalembedding may offer different capabilities or performance characteristics that justify the price difference.

### How does multimodalembedding pricing compare to the average embedding model?

multimodalembedding input pricing is $0.80 per 1M tokens, which is 700% above the median of $0.10 for embedding models. It ranks 140 out of 145 embedding models by input cost, making it cheaper than 3% of models in this category. For output, it costs $0.0000 per 1M tokens compared to the median of $0.0090.

### What makes multimodalembedding different from other Vertex AI models?

Among Vertex AI's 10 embedding models, multimodalembedding ranks 9 by input cost.

### What are the best alternatives to multimodalembedding?

The most comparable embedding models to multimodalembedding are: amazon.titan-embed-image-v1 from AWS Bedrock ($0.80/1M input tokens); amazon.nova-2-multimodal-embeddings-v1:0 from AWS Bedrock ($0.14/1M input tokens); amazon.titan-embed-text-v1 from AWS Bedrock ($0.10/1M input tokens); amazon.titan-embed-g1-text-02 from AWS Bedrock ($0.10/1M input tokens). These alternatives were selected based on similar capabilities, pricing, and provider diversity. You can compare any of these models in detail using the Bifrost Model Library.

### How do I calculate multimodalembedding costs?

multimodalembedding is priced based on input and output tokens, images. Use the interactive calculator at the top of this page to estimate costs for your specific workload. Enter your expected input and output tokens volume and the calculator will show the total cost breakdown. For reference, processing 1M input tokens costs $0.80 and generating 1M output tokens costs $0.0000.

## Related Resources

- [Google Vertex AI models](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/provider/vertex_ai.md)
- [Model library](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library.md)
- [LLM cost calculator](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator.md)
- [Docs: Bifrost docs](https://docs.getbifrost.ai)
- [GitHub: maximhq/bifrost](https://github.com/maximhq/bifrost)
- [Pricing: Bifrost pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/pricing.md)
- [Enterprise: Bifrost enterprise](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/enterprise)
- [Book a Demo: Bifrost demo](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/book-a-demo)
- [Resources: Bifrost resources](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources.md)

---

*This is a markdown version of [https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/vertex_ai/multimodalembedding](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/vertex_ai/multimodalembedding) for AI/LLM consumption.*
