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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
Price as of 2026-05-08 · Source: google_gemini_official_pricing
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Google Gemini text embedding model for retrieval, semantic matching, and classification.
gemini-embedding-001 is a Text model from Google (US). HotON.ai tracks it at $0.15 per 1M input tokens and $0.00 per 1M output tokens, with a 1K-token context window. Its composite efficiency score is 88/100 at an estimated $0.000 per successful task.
gemini-embedding-001 is tracked at $0.15 per 1M input tokens and $0.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.04 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.
gemini-embedding-001 supports up to a 1K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, gemini-embedding-001 is cheaper than 70% of models on input price and ranks #340 of 535 by overall efficiency.
Yes — morph-rerank-v3 is a lower-cost option at $0.00 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
Ready to paste into articles, papers or AI prompts — prices and date refresh with the live data.
HotON.ai — gemini-embedding-001 (Google): $0.15/1M input, $0.00/1M output, as of 2026-05-08. https://hoton.ai/en/models/google-gemini-embedding-001Pricing 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.