Xiaomi MiMo Token Plan Pricing: 2026 Tier Guide for Coding Agents

Xiaomi has pushed deeper into cloud AI coding with the MiMo Token Plan, a four-tier credit subscription that powers MiMo-V2.5-series models inside agent toolchains such as OpenCode, OpenClaw, Claude Code and Codex-class environments. For engineering leads and individual developers who want predictable spend instead of opaque rate limits, the plan’s fixed monthly or annual Credits, published burn ratios and hard stop-then-pay-as-you-go design are the main story—not free open-weight downloads.

The offering arrives amid rapid agent adoption and Chinese cloud price pressure. After a permanent commercial reset on 27 May 2026, Xiaomi cut V2.5 API prices and lifted Token Plan usable volume roughly five- to eightfold at the same list prices, with a one-time credit reset for in-term packages. Older mimo-v2-* models were deprecated on 30 June 2026. Live documentation last updated 15 July 2026 is the baseline for every figure below.

Full pricing: monthly and annual

Annual prepaid equals exactly 12× monthly credits and is priced at about 88% of twelve continuous monthly list payments—roughly a 12% discount. Xiaomi positions Lite for first-time explorers, Standard for frequent efficiency users, Pro for daily professional agent work, and Max for high-intensity “AI as core productivity.” Annual task volume is described as about 12× the monthly marketing rounds.

Do not mix these figures with the original launch buckets (Lite 60M through Max 1.6B credits). Those pre-optimization numbers are obsolete for current purchasing decisions.

Credits are not tokens: model burn rates

Billing is credit-based. All six supported models share one package pool at different ratios: mimo-v2.5-pro, mimo-v2.5, mimo-v2.5-asr, and the TTS family (tts, voiceclone, voicedesign). TTS is limited-time free and does not burn package credits. ASR costs 30 million credits per hour of input audio (second-accurate).

Cache hits are orders of magnitude cheaper than misses and outputs. Official Lite example: 10 million cache-miss input tokens on mimo-v2.5-pro burn 3B credits, leaving roughly 1.1B on a 4.1B plan. ASR-only on Lite yields about 136.6 hours of audio per month (~4.5 hours/day).

Illustrative session math (approximate, not vendor-defined): a mid-size turn of ~20k cache-miss input + 5k output costs about 3M credits on V2.5 versus 9M on Pro. Model choice therefore moves cost more than tier choice. Marketing “rounds” assume mimo-v2.5 medium–complex agent tasks; long-context tool loops on Pro exhaust credits far faster. Community stress tests that report tens of millions of raw tokens on a $6 Lite plan are useful only if readers remember credits ≠ tokens.

C
Shared package pool
E
G
A
Hard stop
Upgrade by price difference
Pay-as-you-go API

Hard limits, exhaustion and pay-as-you-go

A package starts immediately. Monthly validity is purchase day plus 30 full calendar days to 23:59:59 UTC; annual is a calendar year from purchase. Only one package may be active. Upgrades are allowed by paying the price difference:

Price difference = New price − (Remaining / Total) × Original price

Downgrades are not supported. Refunds are not supported; unused credits are not refunded. Usage alerts fire at 50% / 90% / 100%. Auto-renew is available (Alipay, WeChat Pay, Xiaomi Pay domestically; Waffo or Stripe overseas) and can be cancelled anytime.

When credits or validity hit zero, service stops. The system does not silently drain account or bonus balance. Continue by upgrading the package or switching to the regular pay-as-you-go API. Approximate PAYG USD list rates:

A separate V2.5-Pro-UltraSpeed SKU sits on the PAYG matrix at higher rates; public Token Plan model lists center on the six V2.5-family entries above.

Scope is strict: package quota is for programming and agent tools only. Using a package tp- key for non-coding automation or custom backends is a violation risking suspension or key ban. Keys and base URLs are region-specific (China, Singapore, Europe) with OpenAI- and Anthropic-compatible paths; all tools share one quota.

Night discount and prepay value

Off-peak window: Beijing 00:00–08:00 (UTC 16:00–24:00). Consumption coefficient: 0.8×—a 20% reduction in credit burn. Fully shifting work into that window stretches a package by up to one-fifth of effective capacity (timezone-dependent for global teams).

First purchase of a package receives 12% off, once per account; continuous annual is already ~12% off monthly list and does not stack the first-purchase promo the same way. Higher tiers improve list dollars per billion credits slightly; the night window improves work per dollar, not the sticker price.

Competitive context

Western coding agents typically sell seat subscriptions with rate or session ceilings. Claude individual coding access commonly sits around $20/month (Pro) and $100–$200/month (Max-class tiers). MiMo’s published edge is arithmetic transparency: fixed credits, explicit Pro versus V2.5 multipliers, hard stop, night 0.8×, and a clean PAYG escape hatch.

Capability, latency, tool reliability and data residency are not settled by price tables. Some teams still prefer higher-priced Western agents for production reliability, while cost-sensitive shops use MiMo for volume agent loops. Open-weight MiMo-V2.5 / V2.5-Pro releases remain a separate CapEx path; Token Plan is the managed, coding-restricted cloud subscription.

Who should buy which tier

Public pages read as developer packages, not multi-seat enterprise SKUs. Shared keys raise ToS and ban risk; teams often need multiple accounts or PAYG.

Bottom line for stack decisions

MiMo Token Plan is a numbers-first coding-agent subscription at $6–$100/month (annual roughly 12% cheaper) with 4.1B–82B monthly credits, a hard stop into upgrade or pay-as-you-go, and night 0.8× stretch for Beijing off-peak work. It is most useful when teams model cost in credits, design for cache hits, stay inside coding-tool scope, and treat open weights as a different product. For CTOs comparing Claude Max-class or Codex-class spend, the plan belongs on the shortlist for transparent quota math—provided quality and reliability are validated against the workloads that actually matter.