--- title: "multimodalembedding@001 - Model Details & Comparison" description: "multimodalembedding@001 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-001" markdown: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/vertex_ai/multimodalembedding-001.md" --- # multimodalembedding@001 - Model Details & Comparison > multimodalembedding@001 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@001 multimodalembedding@001 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 141 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@001 Pricing Overview At $0.80 per 1M input tokens and $0.0000 per 1M output tokens, multimodalembedding@001 ranks 141 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@001 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@001 costs](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/vertex_ai/model/multimodalembedding-001.md) - [All Vertex AI pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/vertex_ai.md) ## FAQ ### Is multimodalembedding@001 cheaper than amazon.titan-embed-image-v1? No. multimodalembedding@001 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@001 may offer different capabilities or performance characteristics that justify the price difference. ### How does multimodalembedding@001 pricing compare to the average embedding model? multimodalembedding@001 input pricing is $0.80 per 1M tokens, which is 700% above the median of $0.10 for embedding models. It ranks 141 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@001 different from other Vertex AI models? Among Vertex AI's 10 embedding models, multimodalembedding@001 ranks 10 by input cost. ### What are the best alternatives to multimodalembedding@001? The most comparable embedding models to multimodalembedding@001 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@001 costs? multimodalembedding@001 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-001](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/vertex_ai/multimodalembedding-001) for AI/LLM consumption.*