--- title: "gemini-embedding-001 Cost Calculator - Vercel Ai Gateway" description: "Calculate the cost of using gemini-embedding-001 from Vercel Ai Gateway. Input costs $0.15 and output $0.0000 per 1M tokens." url: "https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/gemini-embedding-001" markdown: "https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/gemini-embedding-001.md" --- # gemini-embedding-001 Cost Calculator - Vercel Ai Gateway > Calculate the cost of using gemini-embedding-001 from Vercel Ai Gateway. Input costs $0.15 and output $0.0000 per 1M tokens. ## Important Links - [View MCP Gateway](https://www.getmaxim.ai/bifrost/resources/mcp-gateway.md) - [Features](https://www.getmaxim.ai/bifrost/#features) - [Enterprise](https://www.getmaxim.ai/bifrost/enterprise) - [Pricing](https://www.getmaxim.ai/bifrost/pricing.md) - [Docs](https://docs.getbifrost.ai) - [GitHub](https://github.com/maximhq/bifrost) - [Book a Demo](https://www.getmaxim.ai/bifrost/book-a-demo) ## About gemini-embedding-001 gemini-embedding-001 is an embedding model from Vercel Ai Gateway, one of 6 embedding models they offer. It is priced at $0.15 per 1M input tokens and $0.0000 per 1M output tokens, ranking 120 out of 144 embedding models by cost and cheaper than 15% of models in this category. It accepts up to 0K input tokens. ## Pricing Published Vercel Ai Gateway pricing for gemini-embedding-001. - **$0.15 / 1M tokens Input.** - **$0.0000 / 1M tokens Output.** ## Technical Specifications - **Embedding Mode.** - **0 Max Input Tokens.** - **0 Max Output Tokens.** - **0 Max Tokens.** ## How Pricing Compares At $0.15 per 1M input tokens and $0.0000 per 1M output tokens, gemini-embedding-001 ranks 120 out of 144 embedding models by input cost. It is more expensive compared to the median of $0.10 for embedding models, and is cheaper than 15% of models in this category. | Model | Provider | Input $/1M | Output $/1M | vs gemini-embedding-001 | | --- | --- | --- | --- | --- | | amazon.nova-2-multimodal-embeddings-v1:0 | AWS Bedrock | $0.14 | $0.0000 | -10% | | text-embedding-3-large | Azure | $0.13 | $0.0000 | -13% | | databricks-gte-large-en | Databricks | $0.13 | $0.0000 | -13% | | gemini-embedding-001 | Vertex AI | $0.15 | $0.0000 | 0% | | gemini-embedding-001 | Google Gemini | $0.15 | $0.0000 | 0% | ## More from Vercel Ai Gateway - [text-embedding-3-large ($0.13/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/text-embedding-3-large.md) - [text-embedding-ada-002 ($0.10/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/text-embedding-ada-002.md) - [text-embedding-005 ($0.02/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/text-embedding-005.md) - [text-multilingual-embedding-002 ($0.02/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/text-multilingual-embedding-002.md) ## Related Resources - [All Vercel Ai Gateway pricing](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway.md) ## FAQ ### Is gemini-embedding-001 cheaper than amazon.nova-2-multimodal-embeddings-v1:0? No. gemini-embedding-001 costs $0.15 per 1M input tokens while amazon.nova-2-multimodal-embeddings-v1:0 costs $0.14 per 1M input tokens, making amazon.nova-2-multimodal-embeddings-v1:0 10% more affordable for input. However, gemini-embedding-001 may offer different capabilities or performance characteristics that justify the price difference. ### How does gemini-embedding-001 pricing compare to the average embedding model? gemini-embedding-001 input pricing is $0.15 per 1M tokens, which is 50% above the median of $0.10 for embedding models. It ranks 120 out of 144 embedding models by input cost, making it cheaper than 15% of models in this category. For output, it costs $0.0000 per 1M tokens compared to the median of $0.02. ### What makes gemini-embedding-001 different from other Vercel Ai Gateway models? Among Vercel Ai Gateway's 6 embedding models, gemini-embedding-001 ranks 6 by input cost. ### What are the best alternatives to gemini-embedding-001? The most comparable embedding models to gemini-embedding-001 are: amazon.nova-2-multimodal-embeddings-v1:0 from AWS Bedrock ($0.14/1M input tokens); text-embedding-3-large from Azure ($0.13/1M input tokens); databricks-gte-large-en from Databricks ($0.13/1M input tokens); gemini-embedding-001 from Vertex AI ($0.15/1M 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 gemini-embedding-001 costs? gemini-embedding-001 is priced based on input and output tokens. 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 $0.15 and generating 1M output tokens costs $0.0000. ## Related Resources - [All Vercel Ai Gateway pricing](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway.md) - [LLM cost calculator](https://www.getmaxim.ai/bifrost/llm-cost-calculator.md) - [Model library](https://www.getmaxim.ai/bifrost/model-library.md) - [Docs: Bifrost docs](https://docs.getbifrost.ai) - [GitHub: maximhq/bifrost](https://github.com/maximhq/bifrost) - [Pricing: Bifrost pricing](https://www.getmaxim.ai/bifrost/pricing.md) - [Enterprise: Bifrost enterprise](https://www.getmaxim.ai/bifrost/enterprise) - [Book a Demo: Bifrost demo](https://www.getmaxim.ai/bifrost/book-a-demo) - [Resources: Bifrost resources](https://www.getmaxim.ai/bifrost/resources.md) --- *This is a markdown version of [https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/gemini-embedding-001](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/vercel_ai_gateway/model/gemini-embedding-001) for AI/LLM consumption.*