Xiaomi

MiMo V2.6 Flash

Xiaomi

MiMo V2.6 Flash is Xiaomi’s lower-compute multimodal agent tier. Its sparse model has 309B total parameters and 15B active per token, with native text, image, audio, and video understanding and a 1M context window. Reinforcement learning scales task environments and feedback across coding, general work, visual tasks, and security research. MIT-licensed weights and hosted inference support private deployment and API applications. Subsequent MOPD checkpoints are documented variants of the same named tier.

MiMo V2.6 Pro

Xiaomi

MiMo V2.6 Pro extends Xiaomi’s flagship into native multimodal agent reasoning over text, images, audio, and video. It retains a 1.02T sparse backbone with 42B active parameters and a 1M-token context. Large-scale reinforcement learning uses verifiable coding, knowledge-work, visual, and security environments. API access and MIT-licensed RL checkpoints were released together. Later MOPD refinements and UltraSpeed serving are grouped as variants; benchmark results depend on the chosen checkpoint and agent harness.

MiMo V2.5 Pro

Xiaomi

MiMo V2.5 Pro is Xiaomi’s text-only flagship for complex coding and sustained agent workflows. It has approximately 1.02T total parameters and 42B active parameters, with hybrid sliding-window attention supporting 1M context. The public API beta preceded the April 27 publication of MIT-licensed base and post-trained weights. Pro and the native multimodal V2.5 tier are separate models. UltraSpeed and FP4 serving options retain this identity rather than creating additional model pages.

MiMo V2.5

Xiaomi

MiMo V2.5 is Xiaomi’s full-modal language model with text, image, audio, and video understanding. Its sparse backbone has approximately 310B parameters and activates 15B per token, supporting a 1M-token context. It targets general agents, cross-modal reasoning, and tool-driven workflows. Public API testing preceded the April 27 weight publication. Both base and post-trained weights are now MIT-licensed; quantized serving and draft models are grouped rather than treated as new identities.

MiMo V2 Omni

Xiaomi

MiMo V2 Omni is Xiaomi’s native multimodal model for visual, audio, video, and text understanding. It combines modality encoders with a shared language backbone so an agent can ground its responses in screenshots, recordings, and other inputs. Hosted inference supports reasoning and structured tool use. It is a distinct multimodal tier of the V2 generation, with parameter counts left unspecified because the launch materials do not disclose a reliable total. Its availability does not imply downloadable weights.

MiMo V2 Pro

Xiaomi

MiMo V2 Pro is Xiaomi’s hosted flagship for long-running software engineering and agent tasks. Its trillion-scale sparse backbone activates approximately 42B parameters and combines sliding-window and global attention. The text model supports up to 1M tokens and structured tool use. Anonymous evaluation names such as Hunter Alpha are aliases, rather than separate releases. Xiaomi provides API and chat access; the V2 Pro weights were not publicly released alongside the later V2.5 family.

MiMo V2 Flash

Xiaomi

MiMo V2 Flash is Xiaomi’s open-weight sparse language model for efficient reasoning, coding, and tool-using agents. It has 309B total parameters and 15B active per token, with hybrid attention and multi-token prediction improving serving efficiency. Downloadable base and post-trained weights use MIT licensing. A 256K context accommodates large codebases and documents. The active parameter count describes computation per token; deployment still needs storage for the entire sparse model.