Context Window

Compare

Labs Leanstral 1 5 1 vs MiMo-V2.6-Pro-UltraSpeed

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Mistral

Model

Labs Leanstral 1 5 1

Tool calling

Context window

262K

262,144 tokens · ~197K words

Model page
Xiaomi

Model

MiMo-V2.6-Pro-UltraSpeed

Image inputTool calling

Context window

1.0M

1,048,576 tokens · ~786K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Labs Leanstral 1 5 1262K
MiMo-V2.6-Pro-UltraSpeed1.0M

MiMo-V2.6-Pro-UltraSpeed has about 4× the context window of the other in this pair.

Token calculator →Memory savings →

MiMo-V2.6-Pro-UltraSpeed has 300% more context capacity (1048K vs 262K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use MiMo-V2.6-Pro-UltraSpeed. Its 1048K context fits entire documents without chunking (vs 262K).

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecLabs Leanstral 1 5 1MiMo-V2.6-Pro-UltraSpeed
Context window262,144 tokens (262K)1,048,576 tokens (1048K)
Max output tokens131,072 tokens (131K)131,072 tokens (131K)
Speed tierBalancedBalanced
VisionNoYes
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoYes
Batch APINoNo
Release dateN/ASep 2026

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderLabs Leanstral 1 5 1 inLabs Leanstral 1 5 1 outMiMo-V2.6-Pro-UltraSpeed inMiMo-V2.6-Pro-UltraSpeed out
Mistral————
Openrouter——$4.35/M$8.70/M

Frequently asked questions

MiMo-V2.6-Pro-UltraSpeed has a larger context window: 1048K tokens vs 262K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Calculate your savingsLearn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model