Xiaomi: MiMo-V2.5 API Pricing
Xiaomi: MiMo-V2.5 costs $0.119 per 1M input tokens and $0.238 per 1M output tokens (cache reads: $0.0026). Context window: 1.1M. Prices verified 2026-10-21 · source
Alternatives to consider
45% cheaper with nearly identical quality (41.8 vs 38)
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Token economics
| Token type | Price | vs base input |
|---|---|---|
| Standard input | $0.119 | — |
| Cache read | $0.0026 | −98% |
| Output | $0.238 | — |
Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.
Higher effort = deeper thinking = more reasoning tokens billed as output.
What would Xiaomi: MiMo-V2.5 cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $1.90 |
| Coding agent | 5,000 | 8,000 / 2,000 | $7.14 |
| RAG pipeline | 30,000 | 4,000 / 500 | $17.85 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $5.24 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About Xiaomi: MiMo-V2.5
MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...
Compare Xiaomi: MiMo-V2.5 with
- Xiaomi: MiMo-V2.5 vs OpenAI: GPT-5.6 Terra Pro
- Xiaomi: MiMo-V2.5 vs Anthropic: Claude Fable 5
- Xiaomi: MiMo-V2.5 vs Anthropic: Claude Opus 5
- Xiaomi: MiMo-V2.5 vs OpenAI: GPT-5.6 Sol
Popular head-to-heads — see all on the comparisons index.
Frequently asked questions
How much does Xiaomi: MiMo-V2.5 cost?
Xiaomi: MiMo-V2.5 costs $0.119 per 1M input tokens and $0.238 per 1M output tokens; cached input tokens cost $0.0026 per 1M. Verified 2026-10-21 — provider source.
What is the context window?
1.1M tokens, with up to 945K output tokens per response. That's roughly 1313 pages of text in a single request.
Does it support prompt caching?
Yes — cached input is $0.0026/1M, about 98% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.
What's a cheaper alternative?
ScaleDown: Summarize saves about 81% on a typical workload with comparable quality.
Official resources
- Xiaomi: MiMo-V2.5 on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis benchmarks → — independent intelligence and performance analysis.
- Shred your current bill — paste a CSV and see if switching saves money.