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Xiaomi MiMo V2.5 Pro

Alibaba Cloud Model Studio · Xiaomi (≤256K tier) · Xiaomi open-source, Reasoning model

Text Xiaomi open-sourceReasoning model

MiMo V2.5 Pro is Xiaomi's open-source reasoning model, served on Alibaba Cloud Model Studio at the ≤256K input tier. It is a text model with a 1000K context window, priced per 1M tokens in CNY.

API pricing (official list price, CNY per 1M tokens)

Input (cache miss)¥7
Output¥21
Cache hitNot published
Time-based pricing Single price around the clock
Billing currencyCNY (Chinese yuan) — the vendor's original billing currency, not converted

Specifications

Context window1000K tokens
ModalitiesText
Noted featuresXiaomi open-source, Reasoning model
Vendor / channelAlibaba Cloud Model Studio · Xiaomi (≤256K tier)
Price sourceAlibaba Cloud Model Studio pricing
Verified2026-09-18

Site calculation: estimated monthly cost at default usage

Site calculation, not a vendor quote. Assumptions: 100 calls/day · 2000 input / 800 output tokens per call · 30-day month · 30% cache hit rate. Same formula as the cost calculator.

Effective input priceNo published cache price; input billed at ¥7
Input cost100 × 30 × (2000 ÷ 1,000,000) × 7 = ¥42.00
Output cost100 × 30 × (800 ÷ 1,000,000) × ¥21 = ¥50.40
Estimated monthly cost¥92.40

Notes and limitations

· Prices are official published list prices per 1M tokens in the original billing currency (here CNY). Limited-time promotions, resource packs and subscription discounts are not included; the vendor's console prevails.

· "Verified" is the date this page's figures were last checked against the official source linked above. Pricing changes over time — confirm on the source page before making decisions.

· The monthly cost above is this site's own calculation under fixed usage assumptions. It is not a vendor quote and does not constitute purchase advice.

· This page records no benchmark results and claims no leadership on any task. Editor's note: this page records official pricing and specifications only and makes no quality or performance ranking claims. Evaluate output quality on your own workloads before committing.

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