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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 2026-05-10 · Source: voyage_official_pricing
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Voyage Context 3 creates contextualized chunk embeddings for document retrieval and long-context RAG pipelines.
voyage-context-3 is a Text model from Voyage AI (US). HotON.ai tracks it at $0.18 per 1M input tokens and $0.00 per 1M output tokens, with a 32K-token context window. Its composite efficiency score is 89/100 at an estimated $0.000 per successful task.
voyage-context-3 is tracked at $0.18 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.
voyage-context-3 supports up to a 32K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, voyage-context-3 is cheaper than 69% of models on input price and ranks #269 of 537 by overall efficiency.
Yes — qwen3-235b-a22b-2507 is a lower-cost option at $0.10 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 — voyage-context-3 (Voyage AI): $0.18/1M input, $0.00/1M output, as of 2026-05-10. https://hoton.ai/en/models/voyage-voyage-context-3Pricing 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.