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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 2026-05-11 · Source: allenai_reference_catalog
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Olmo 3 32B Think is a large-scale, 32-billion-parameter model purpose-built for deep reasoning, complex logic chains and advanced instruction-following scenarios. Its capacity enables strong performance on demanding e...
olmo-3-32b-think is a Text model from Allenai (US). HotON.ai tracks it at $0.15 per 1M input tokens and $0.50 per 1M output tokens, with a 66K-token context window. Its composite efficiency score is 89/100 at an estimated $0.001 per successful task.
olmo-3-32b-think is tracked at $0.15 per 1M input tokens and $0.50 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.41 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.
olmo-3-32b-think supports up to a 66K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, olmo-3-32b-think is cheaper than 70% of models on input price and ranks #215 of 537 by overall efficiency.
Yes — deepseek/deepseek-v4-flash is a lower-cost option at $0.28 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
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HotON.ai — olmo-3-32b-think (Allenai): $0.15/1M input, $0.50/1M output, as of 2026-05-11. https://hoton.ai/en/models/allenai-olmo-3-32b-thinkPricing 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.