Tasks and inputs
MiMo-V2.6-Distill-Qwen-9B is listed for Image-text-to-text, Text generation, Coding & Code Generation. It accepts text, image and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 13, 2026
MiMo-V2.6-Distill-Qwen-9B is Xiaomi’s smaller downloadable checkpoint for agent research and reinforcement-learning experiments.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Xiaomi released this distilled Qwen checkpoint with the MiMo-V2.6 family and its reinforcement-learning resources. It is intended as a more accessible model for experiments around agent tasks and training. It should not be substituted for the much larger V2.6 Pro or Flash models when interpreting a benchmark result.
Use the exact XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B checkpoint and its documented runtime configuration. Pin the model revision, prompting template and evaluation environment. For training experiments, retain the starting checkpoint, reward definitions and task set so that an improvement can be reproduced rather than inferred from a single successful rollout.
Downloadable weights are available, but a dedicated first-party API route and token price have not been established for this distilled checkpoint. The Pro and Flash API prices do not apply to it. Check the checkpoint licence and your local memory and hardware requirements before deciding on an inference or training setup.
Build a small evaluation set from the work your application actually handles. Include incomplete information, contradictory inputs and a case that should stop for clarification. Define an acceptable deliverable before running the model, then inspect failures as carefully as successful examples. Keep input material, tools and effort settings consistent when comparing candidates.
Record the exact model identifier, deployment route and request settings with each result. Count complete runs, including rejected outputs, retries and tool calls. When the workflow creates files or code, open the files or execute the existing checks before accepting the result. A plausible first response can hide an incomplete final deliverable.
The specifications describe supported interfaces and request capacity. They do not establish a measured quality ranking or a latency guarantee for your account. SyncDev has not independently benchmarked this model. Choose a deployment after testing the languages, input formats and operating conditions that matter to your users.
Explore xiaomi models, browse model tasks, or compare two models with the same acceptance criteria.
Compare the model on the work you need to complete.
MiMo-V2.6-Distill-Qwen-9B is listed for Image-text-to-text, Text generation, Coding & Code Generation. It accepts text, image and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
The weights are downloadable under MIT. Check runtime support and size the complete model and working context for your expected concurrency.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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