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This article identifies and provides fixes for three bugs encountered when serving the MiMo-V2.6-Flash model with vLLM, including empty responses in streaming mode, reasoning loss in tool loops, and a hidden token output cap.
MiMo-V2.6 has been distilled into Qwen 9B, creating a more efficient version of the Qwen model released on Hugging Face.
Peano Labs has scaled reinforcement learning on TPUs for the MiMo model family, enabling full-parameter RL at 310B parameters with Jax, where scaling is primarily a configuration change.
This article compares the performance of MiMo-V2.6-Flash-RL with open-weight models using Terminal-Bench 4.0 results, showing MiMo's competitive scores.
mimofan v0.0.17 is a Rust terminal AI coding assistant released with native support for MiMo and DeepSeek models, featuring security audit gates, memory enhancements, protocol improvements, and subagent orchestration.
This paper proposes NN-CLEAN, a hybrid framework that embeds a multi-head residual network into the iterative CLEAN extraction loop for efficient multipath parameter estimation in low-SNR channel modeling. It matches traditional Grid-Search CLEAN accuracy while greatly reducing computational complexity and enabling parallelization for real-time MIMO systems.
Proposes a deep wireless physical neural network where multi-hop MIMO relays realize trainable linear transforms and power amplifier nonlinearities serve as activation functions, enabling over-the-air inference for image classification.
A free online textbook covering the fundamentals of wireless communication, including MIMO, space-time coding, OFDM, and CDMA, intended for graduate students and practicing engineers.
Xiaomi has quietly released MiMo-V2.5-DFlash, a 300B-parameter model on Hugging Face, with DFlash potentially doubling inference speed.
MiMo v2.5 is praised for its impressive token generation speed in OpenCode, suggesting it's an underrated model update.
Mimo and DeepSeek have optimized AI models to achieve low pricing with 2-3x profit margins, as detailed in their official blog.
Recommend the Opencode go plan. First month $5, supports Alipay. Use mimo 2.5 or deepseek v4pro models. Configure on Hermes to handle daily tasks via phone, and use Codex for complex tasks.
MiMo-V2.5-Pro-UltraSpeed is a fast model that can generate animated demonstrations of the quicksort algorithm.
Xiaomi MiMo thanks @cline for their partnership, celebrating the rise of open-weights and developers building on MiMo.
This paper presents Agentic-LTPO, a nested bilevel optimization framework that uses agentic AI to adapt physical layer configurations under dynamic operator policies, achieving 57.2% long-term performance improvement in cell-free MIMO beamforming.
The Stepfun Open Platform has launched a new step plan package, offering a 15-day free trial. Both new and existing users can participate, and inviting friends can extend the trial period.
Compares the speed performance of Kimi K2.7 Code HighSpeed (180-260 t/s) and MiMo Ultra-High-Speed (1000+ t/s) on coding tasks, pointing out that MiMo has overwhelming speed and strong quality, suitable for use with Claude Code.
Xiaomi launches internal test of MiMo-V2.5-Pro-UltraSpeed model, with peak speed of 1000 tokens/s, aiming to boost the productivity of Coding Agent. Trial resources are limited and directed to professional institutions.
A discussion comparing DeepSeek V4 Pro, MiMo-V2.5-Pro, and MiniMax M3 for best value in local or openrouter use, with a focus on agentic and coding tasks, and mentions of Hermes Agent and Qwen 3.6 variants.
The DeepSWE benchmark costs are per task, not per total run. Running models like Mimo V2.5 Pro can cost ~$225 for a full run, while Mimo V2.5 non-pro costs ~$7.15. Users should be aware of this before running expensive models.