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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: xiaomi_reference_catalog
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
MiMo-V2-Flash is an open-source foundation language model developed by Xiaomi. It is a Mixture-of-Experts model with 309B total parameters and 15B active parameters, adopting hybrid attention architecture. MiMo-V2-Fla...
mimo-v2-flash is a Text model from Xiaomi (CN). HotON.ai tracks it at $0.09 per 1M input tokens and $0.29 per 1M output tokens, with a 262K-token context window. Its composite efficiency score is 90/100 at an estimated $0.000 per successful task.
mimo-v2-flash is tracked at $0.09 per 1M input tokens and $0.29 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.24 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.
mimo-v2-flash supports up to a 262K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, mimo-v2-flash is cheaper than 84% of models on input price and ranks #113 of 535 by overall efficiency.
Yes — ling-2.6-flash is a lower-cost option at $0.24 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 — mimo-v2-flash (Xiaomi): $0.09/1M input, $0.29/1M output, as of 2026-05-11. https://hoton.ai/en/models/xiaomi-mimo-v2-flashPricing 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.