Xiaomi MiMo-V2.6-Pro
Xiaomi MiMo-V2.6-Pro publishes its weights, but at 1020B parameters (42B active per token) no consumer machine holds the checkpoint. This page covers the access paths that work and the open models that actually run locally.
Why you can't run Xiaomi MiMo-V2.6-Pro locally
At 1020B parameters (42B active per token), a Q4-class build of Xiaomi MiMo-V2.6-Pro would need roughly 612 GB, beyond any consumer machine. That figure is arithmetic, not opinion: 0.6 GB per billion parameters is the standard Q4 rule we apply across the whole catalog. The weights themselves are public (official source linked below); capacity, not licensing, is the wall.
What works instead: the hosted API. For most workloads, the open models below deliver the same job on hardware that fits under a desk.
Sept 21, 2026 Xiaomi flagship (MIT, XiaomiMiMo/MiMo-V2.6-Pro-RL on HF). Sparse MoE with 1.02T total / 42B activated parameters, omnimodal input and 1M tokens of context. Open weights, but beyond any consumer machine: API or a multi-GPU server.
What to run locally instead of Xiaomi MiMo-V2.6-Pro
More MiMo models
Frequently asked questions
Can I run Xiaomi MiMo-V2.6-Pro locally?
Not on hardware you can buy. The weights are public, but Xiaomi MiMo-V2.6-Pro is a 1020B-parameter model (42B active), and a Q4-class build would need roughly 612 GB, beyond any consumer machine. Until the ecosystem ships a smaller official build, the API or a smaller open model is the practical path.
How do I access Xiaomi MiMo-V2.6-Pro?
Through the vendor's hosted API. The official source is linked on this page.
What is the best local alternative to Xiaomi MiMo-V2.6-Pro?
Qwen3 235B A22B is the strongest local model we track (235B, from 192 GB machines), with Qwen3.5 122B-A10B Instruct close behind. Both run on a single high-memory Mac or GPU, see their pages for exact hardware.
Cite this page
ModelFit: Xiaomi MiMo-V2.6-Pro, specs, memory math and hardware verdicts. https://modelfit.io/models/mimo-v2.6-pro/ (dataset updated 2026-09-29, CC BY 4.0).