China AI

AIZ.ai's GLM-5.3 delivers a 50% coding gain over GLM-5.2 on Z.ai Code Bench, reaching open-source state-of-the-art on public benchmarks including Terminal Bench 3.0.

AIZ.ai has released GLM-5.1, its next-generation flagship model for agentic engineering, with stronger coding than GLM-5.

Why it matters: The release gives benchmark tables against several rival models, letting readers compare GLM-5.1's coding and agentic results with GLM-5 and frontier systems.

AIXiaomi released the MiMo-V2.5-TTS Series, three speech synthesis models for stock voices, voice design, and voice cloning.

Why it matters: The release shows how a TTS family adds style instructions, inline audio tags, and voice design or cloning to speech synthesis, which matters for agent and creative workflows.

AIXiaomi MiMo has released MiMo-V2.5-ASR, an open-source speech recognition model that the company says achieves state-of-the-art results across multiple benchmarks.

AIAlibaba NLP released LaSER-Qwen3-8B, an 8B-parameter dense retriever built on Qwen/Qwen3-8B that internalizes explicit reasoning into latent space through continuous latent thinking tokens.

AIAman Sanger says Cursor's team evaluated many base models on perplexity-based evals and found Kimi k2.5 the strongest.

AIXiaomi introduces MiMo-V2-Omni, a single model that fuses image, video, and audio encoders into a shared backbone with native tool calling and UI grounding.

Why it matters: The page gives benchmark comparisons, a driving-risk demo, and browser-task walkthroughs, letting readers check how far the omni-modal claims extend into agent use.

AIMiniMax says M2.7 is its first model to deeply participate in its own evolution, building agent harnesses and running reinforcement learning experiment workflows.

Why it matters: The post ties M2.7's self-evolution claims to specific benchmark numbers and workflow details, helping readers judge how much of the iteration loop is autonomous.

AIXiaomi announced MiMo-V2-Pro, a flagship foundation model for agent workloads with over 1T total parameters, 42B active, and up to 1M-token context.

Why it matters: The post gives benchmark placements, parameter scale, context length, and tiered API pricing, so readers can compare it against Claude and GPT models on concrete terms.

AIXiaomi has launched MiMo-V2-TTS, a speech synthesis model that lets users describe the desired voice style in plain language.

Why it matters: The source gives concrete controls for emotion, dialect, singing, and non-verbal sounds, showing how a voice model can be directed through plain-language style prompts.

AIApple has released apple/SimpleSD-30B-instruct, a research checkpoint built on Qwen that uses Simple Self-Distillation to improve code generation without rewards, verifiers, or teacher models.

AIApple has published SimpleSD-4B-thinking on Hugging Face, a research checkpoint built on Qwen that improves code generation through Simple Self-Distillation without rewards, verifiers, teacher models, or reinforcement learning.

AIApple has released SimpleSD-4B-instruct on Hugging Face, a research checkpoint fine-tuned from Qwen3-4B-Instruct-2507 on its own sampled outputs to improve code generation.

AITri Dao announced Mamba-3, which he described as the most powerful linear sequence model to date, as hybrid architectures increasingly rely on strong linear models.

AIBAAI has released RoboBrain-Dex, a dexterous manipulation model for embodied intelligence trained on large-scale, diverse human egocentric data rather than massive robot teleoperation datasets.

AIFun-CineForge, from FunAudioLLM, is an open-source toolkit with an end-to-end dataset pipeline and an MLLM-based model for zero-shot movie dubbing across diverse cinematic scenes.

AIChina's Ministry of Industry and Information Technology launches the Industrial Data Foundation Action, a pilot program to build high-quality industry datasets for AI. Consortia led by key industrial firms, platform institutions, advanced manufacturing clusters and SME digital transformation pilot cities will develop data platforms, standards and datasets, with the goal of building a batch of such datasets by the end of 2026.

AIChina's Ministry of Industry and Information Technology (MIIT) has published a list of 28 typical cases of digital empowerment for reducing grassroots burdens.

AIMiniMax describes Forge, its internal reinforcement learning framework for training real-world agents, which was used during the development of MiniMax M2.5.

Why it matters: The post details how the Forge framework balances throughput, stability, and agent flexibility, with concrete scheduling and prefix-merging methods for training agent RL at scale.

AIMiniMax has released M2.5, which it says reaches 80.2% on SWE-Bench Verified and 76.3% on BrowseComp with context management.

Why it matters: The source gives benchmark scores against Claude and GPT models plus per-task token and runtime figures, so readers can weigh the cost-speed tradeoff directly.

AIZ.ai's release notes list GLM-5.3-Flash, a hybrid-architecture model with 320B total parameters and 18B activated, and GLM-5.3, which the company says achieves a 50% gain over GLM-5.2 on Z.ai Code Bench.

AIZ.ai launches GLM-5, scaling from 355B to 744B total parameters with 40B active and pre-training data from 23T to 28.5T tokens.

Why it matters: The source gives concrete scale, data, and benchmark comparisons against named frontier models, showing where GLM-5 sits among open-source and proprietary systems.

AIShanghai AI Laboratory has published its Intern-S1-Pro model on ModelScope, linked from the post. The post provides no further details on architecture, parameter count, benchmarks, or licensing.

AIZ.ai has launched GLM-OCR, a compact, high-performance optical character recognition model built on its self-developed CogViT and GLM-0.5B encoder-decoder architecture.

AIThe Beijing Academy of Artificial Intelligence (BAAI) published its Emu3 multimodal large model research in Nature, which the post describes as the first large-model achievement led by a Chinese research institution in that journal.

AIZ.ai has released GLM-OCR, a 0.9B-parameter multimodal OCR model for complex document understanding, under the MIT License.

Why it matters: The page gives benchmark scores, a 0.9B parameter size, and supported serving frameworks, which help readers weigh OCR deployment options against heavier alternatives.

AIBAAI released RoboBrain 2.5, an embodied AI model that turns 2D scene understanding into actionable 3D trajectories and provides dense temporal value estimates for real-time progress feedback on long-horizon tasks.

AIBAAI's RoboCOIN is a bimanual robot dataset with more than 180,000 trajectories across 421 tasks, collected from 15 robot platforms in 16 real-world scenarios.

AIZ.ai has released GLM-4.7-Flash, a 30B-A3B MoE model that it positions as the strongest model in the 30B class. The model reports SWE-bench Verified 59.2 and τ²-Bench 79.5, and supports local deployment through vLLM and SGLang.

Why it matters: The source lists benchmark scores against Qwen3-30B-A3B-Thinking-2507 and GPT-OSS-20B, letting readers compare the 30B-class MoE model directly with its named rivals.

AIZ.ai has launched GLM-4.7-Flash, a lightweight, efficient model positioned as the free-tier version of GLM-4.7.

AIBAAI will host a booth at AAAI 2026 in Singapore Expo Hall 3, Booth A47, from January 22 to 25, 9:00 to 17:00.

AIZ.ai has launched GLM-Image, an image generation model built on a multimodal architecture that combines autoregressive semantic understanding with diffusion-based decoding.

AITsinghua AIR and BAAI's DrugCLIP screened 10,000 proteins against 500 million molecules, identifying over 2 million drug candidates.

AIMoonshot AI released Kimi K2.5, an open-source native multimodal agentic model built by continual pretraining on about 15 trillion mixed visual and text tokens.

Why it matters: The model card gives a full benchmark table against GPT-5.2, Claude 4.5 Opus, and Gemini 3 Pro, useful for comparing open multimodal agent models.

AIFunAudioLLM has released Fun-Audio-Chat-8B, a roughly 8B-parameter large audio language model for natural, low-latency voice interaction, under Apache 2.0.

AIXiaomi's MiMo model was evaluated against two comparison models on creative writing and artistic perception tasks, with nine evaluators grading outputs on a 1-to-5 scale.

AIMiniMax has released MiniMax-M2.1 model weights on Hugging Face, with API access on the MiniMax Open Platform and the MiniMax Agent product.

Why it matters: The release pairs open weights with a broad benchmark table against Claude and GPT models, letting readers compare coding and agent claims directly.

AIMiniMax released the technical report and pretrained weights for VTP-Large-f16d64, a visual tokenizer that jointly optimizes contrastive, self-supervised, and reconstruction losses.

AIXiaomi released and open-sourced MiMo-V2-Flash, a Mixture-of-Experts model with 309B total and 15B active parameters, under the MIT license.

Why it matters: The post gives architecture, speculative decoding speedup, and pricing figures, which help readers judge how the efficiency claims are achieved and what they cost.

AIAlibaba's FunAudioLLM released Fun-ASR-MLT-Nano-2512, an 800M-parameter multilingual speech recognition checkpoint on Hugging Face that supports 31 languages, with emphasis on East and Southeast Asian languages.