Calculate the cost of using gte-large from OpenRouter for your AI applications
Pricing data last updated:
Mode: Embedding
Max: 512 tokens
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gte-large is an embedding model from OpenRouter, one of 16 embedding models they offer. It is priced at $0.01 per 1M input tokens, ranking 6 out of 128 embedding models by cost and cheaper than 91% of models in this category. gte-large supports structured output. It accepts up to 1K input tokens.
Note: Use the interactive calculator above to estimate costs for your specific usage patterns.
Use the maximum token limits shown above to understand the model's capacity. This model can handle up to 512 input tokens.
At $0.01 per 1M input tokens, gte-large ranks 6 out of 128 embedding models by input cost. It is more affordable compared to the median of $0.10 for embedding models, and is cheaper than 91% of models in this category.
gte-large is one of 16 OpenRouter embedding models, with support for structured output.
| Model | Provider | Input / 1M tokens | Output / 1M tokens | vs gte-large |
|---|---|---|---|---|
| bge-en-icl | Nebius | $0.01 | $0.0000 | 0% |
| bge-multilingual-gemma2 | Nebius | $0.01 | $0.0000 | 0% |
| e5-mistral-7b-instruct | Nebius | $0.01 | $0.0000 | 0% |
Similar embedding models from other providers
No. gte-large costs $0.01 per 1M input tokens while bge-en-icl costs $0.01 per 1M input tokens, making bge-en-icl 0% more affordable for input. However, gte-large may offer different capabilities or performance characteristics that justify the price difference.
gte-large input pricing is $0.01 per 1M tokens, which is 90% below the median of $0.10 for embedding models. It ranks 6 out of 128 embedding models by input cost, making it cheaper than 91% of models in this category.
Among OpenRouter's 16 embedding models, gte-large ranks 1 by input cost. It is the most affordable OpenRouter model with structured output support.
The most comparable embedding models to gte-large are: bge-en-icl from Nebius ($0.01/1M input tokens); bge-multilingual-gemma2 from Nebius ($0.01/1M input tokens); e5-mistral-7b-instruct from Nebius ($0.01/1M input tokens); bge-m3 from Novita ($0.01/1M 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.
Yes. At $0.01 per 1M input tokens, gte-large is the most affordable embedding model that supports structured output. This makes it a strong option for structured output-dependent workloads where cost efficiency matters.
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gte-large 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.