AI Trend Notifier
EN

$ diff mimo-v2-6-pro muse-spark-1-3

MiMo-V2.6-Pro vs Muse Spark 1.3

Values come from MiMo-V2.6-Pro and Muse Spark 1.3, where each is cited to its source. This page states no benchmark result and ranks neither model — it puts two published specifications next to each other. Where a lab has not published a figure, the row says so rather than guessing.

What actually differs

Context window
Identical — both accept 1M tokens, so context length is not a reason to pick either.
Input price
MiMo-V2.6-Pro at $0.435/M against $1.25/M — 2.9× cheaper to feed. Standard rates: one of these labs also quotes a lower cached-input tier, which applies only when a prefix is reused — see the full spec below.
Output price
MiMo-V2.6-Pro at $0.87/M against $4.25/M — 4.9× cheaper to generate. Output dominates the bill on most agentic workloads, where the model writes far more than it reads.
Weights
MiMo-V2.6-Pro publishes weights (MIT (open weights)); Muse Spark 1.3 is API-only. That decides self-hosting, air-gapped deployment and fine-tuning before any capability question does.
Recency
MiMo-V2.6-Pro shipped 20 days after Muse Spark 1.3 (2026-09-22 vs 2026-09-02).

Full spec

AttributeMiMo-V2.6-ProMuse Spark 1.3
DeveloperXiaomiMeta AI
Released2026-09-222026-09-02
Context window1M tokens1,000,000
Pricingno vendor list price — weights are MIT and self-hostable; routed providers reported at $0.435/M input · $0.87/M outputStandard $1.25/M input · $4.25/M output · Contributor ≈$0.10/M input · ≈$0.20/M output
LicenseMIT (open weights)proprietary
AvailabilityHugging Face as `XiaomiMiMo/MiMo-V2.6-Pro-RL`; hosted via third-party routersMuse Code, Meta Model API

How these pages are produced

← all comparisons