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Daily blended price ($/1M) — recorded each day, builds into a trend over time.
Typical 3:1 output-to-input mix, per 1M tokens
Source: litellm
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Amazon Titan Text Embeddings v2 is a Bedrock embedding model for retrieval and semantic search.
amazon.titan-embed-text-v2:0 is a Text model from AWS Bedrock (US). HotON.ai tracks it at $0.02 per 1M input tokens and $0.00 per 1M output tokens, with a 8K-token context window. Its composite efficiency score is 88/100 at an estimated $0.000 per successful task.
amazon.titan-embed-text-v2:0 is tracked at $0.02 per 1M input tokens and $0.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.01 per 1M tokens. Figures are illustrative demo data.
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
amazon.titan-embed-text-v2:0 supports up to a 8K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, amazon.titan-embed-text-v2:0 is cheaper than 97% of models on input price and ranks #300 of 535 by overall efficiency.
Ready to paste into articles, papers or AI prompts — prices and date refresh with the live data.
HotON.ai — amazon.titan-embed-text-v2:0 (AWS Bedrock): $0.02/1M input, $0.00/1M output. https://hoton.ai/en/models/aws-bedrock-amazon-titan-embed-text-v2-0Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.