MiMo-V2.6-Flash-MOPD
huggingface.co- Category
- Developer Tools
- Rank
- No. 2672Tools index
Previous survey · No. 2575 ·
- Pricing
- Open Source
- Type
- TOOL
- Use case
- Models: Train & Run
- Date
About
MiMo-V2.6-Flash-MOPD is a multimodal large language model from Xiaomi's MiMo team that handles text generation, vision-language understanding, audio, video understanding, and agentic tool calling with long-context support, released under the MIT license. Its architecture combines an LLM backbone with a dedicated MiMo vision encoder, audio encoders, and a speculative decoder, and it can be served through vLLM or SGLang for OpenAI-compatible inference.
At a glance
MiMo-V2.6-Flash-MOPD is Xiaomi’s downloadable multimodal model checkpoint, distilled from several specialist teachers. It is worth benchmarking if you already run large models and want to measure whether the distilled checkpoint improves your agent or multimodal tasks.
Good fit
Inference teams comparing checkpoints on a controlled serving stack.
Consider something else when
Use a hosted endpoint or smaller model if you cannot provision and maintain inference for this checkpoint.
Start here
Read the model card and choose a small evaluation from your actual workload. Compare the checkpoint with your current baseline on quality and serving cost before migrating.
Cost and requirements
The model card lists MIT licensing and an FP8 checkpoint. Hosting needs compatible inference software and hardware sized for the weights, context and concurrent requests.
Limits to know
The model uses a sparse mixture of experts. Activated parameter counts do not describe the full weight footprint. Review any custom model code required by your runtime before enabling it.
Sources checked 2026-11-05. Source-based assessment.
Why it made the leaderboard
Gives developers a lower-latency, MIT-licensed option for running Xiaomi's multimodal agent model locally or via popular inference servers.
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