Quick MiMo Token Usage Guide | Generated by AI

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Question: How can I use the Xiaomi MiMo platform tokens before my Pro monthly plan expires in 2 days?

Answer:

Your plan has 106M tokens used out of 38B — you’ve barely scratched the surface. With 2 days left, here’s how to burn through useful work fast:

High-Value Things to Do Right Now

1. Batch LLM API calls against your existing projects

Point your CLI agents (ww, iclaw, zz) at the MiMo endpoint instead of Anthropic/OpenAI. Check their docs for the base URL:Answer:

Got the docs. The API is OpenAI-compatible, so you can drop it into anything immediately.

Quick Setup

export MIMO_API_KEY="your_key_here"

Base URL: https://api.xiaomimimo.com/v1
Latest model: mimo-v2.5-pro

High-Value Ways to Burn Tokens in 2 Days

Given your profile (CLI agents, blog, notes pipeline), here’s what to actually do:

1. Wire it into your existing CLI agents as a cheap backend

Since it’s OpenAI-compatible, just swap base_url:

from openai import OpenAI

client = OpenAI(
    api_key=os.environ["MIMO_API_KEY"],
    base_url="https://api.xiaomimimo.com/v1"
)

Point ww/zz/iclaw here instead of OpenAI. Zero code change if you’re already using OpenAI SDK.

2. Batch-process your blog posts or notes

You have ~400 blog posts and ~8,000 notes. Run bulk LLM passes on them:

import os, glob
from openai import OpenAI

client = OpenAI(api_key=os.environ["MIMO_API_KEY"], base_url="https://api.xiaomimimo.com/v1")

for post in glob.glob("~/blog/_posts/*.md"):
    with open(post) as f:
        content = f.read()
    resp = client.chat.completions.create(
        model="mimo-v2.5-pro",
        messages=[
            {"role": "user", "content": f"Extract key technical concepts and generate 5 quiz questions:\n\n{content}"}
        ],
        max_completion_tokens=1024
    )
    print(resp.choices[0].message.content)

Ideas: generate flashcards, extract concept graphs, create summaries, find gaps in your notes.

3. Use it as a thinking/reasoning model for math/code problems

MiMo-V2.5-Pro has reasoning capability (reasoning_content field). Good for: algorithm derivation, proof-checking, transformer math you’re studying.

curl -s -X POST 'https://api.xiaomimimo.com/v1/chat/completions' \
  -H "api-key: $MIMO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mimo-v2.5-pro",
    "messages": [{"role":"user","content":"Derive the gradient of cross-entropy loss w.r.t. logits step by step"}],
    "max_completion_tokens": 2048,
    "temperature": 1.0
  }' | jq '.choices[0].message'

4. Hook it into Claude Code / Cline / OpenCode

The docs show a dedicated Claude Code integration page. You can use MiMo as the backend for your agentic coding sessions — free token burn at scale.

Set in your Claude Code config:

{
  "api_url": "https://api.xiaomimimo.com/anthropic",
  "api_key": "your_mimo_key",
  "model": "mimo-v2.5-pro"
}

5. Multimodal / audio (if you have content)

They support image, audio, and video understanding. If you have any recorded talks, code screenshots, or diagrams to process, now’s the time.

TL;DR Priority Order

  1. Swap base_url in your existing agents → instant token consumption on real workloads
  2. Batch your notes/blog through summarization/QA generation pipelines
  3. Run reasoning-heavy tasks (math, architecture design) where you’d normally pay more per token
  4. Configure in Claude Code/Cline as backend for agentic coding

You have ~37.9B tokens remaining — even at aggressive API usage you won’t make a dent in 2 days, so focus on tasks that produce real value, not burning for burning’s sake.

References:

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