#Open source/Repo

AIMistral AI has released mistralai/Mistral-Medium-3.5-128B-EAGLE, an EAGLE draft model for speculative decoding with the 128B dense Mistral Medium 3.5. The companion model, which the source says replaces Mistral Medium 3.1 and Magistral in Le Chat and Devstral 2 in Vibe, has a 256k context window, handles text and image input with text output, and is served with vLLM or SGLang using three speculative tokens. The model is released under a Modified MIT License that allows commercial use with exceptions for companies with large revenue.

AIXiaomi released and open-sourced MiMo-V2.5-Pro, a 1.02T-parameter Mixture-of-Experts model with 42B active parameters and a 1M-token context window. The company reports gains in agentic tasks, software engineering, and long-horizon work, including a Rust SysY compiler task finished in 4.3 hours across 672 tool calls. Weights and tokenizer are on Hugging Face, and API pricing is unchanged.

Why it matters: The release pairs a 1.02T-parameter open-weight model with long-horizon agent results and token-efficiency claims, useful for judging its fit in coding and agent workflows.

AINemotron Hackathon Winners - S Korea

AIApple has released CADD-Base-7B on Hugging Face, a 7B masked diffusion language model for code generation that uses Continuously Augmented Discrete Diffusion (CADD) to guide discrete denoising with a continuous flow-matching signal. The model loads through Transformers with trust_remote_code, and its diffusion_generate method supports CADD sampling modes "weighted" and "argmax" with alg options such as "entropy" and "maskgit_plus". The release builds on DiffuCoder and reuses Dream's modeling architecture and generation utilities.

AIOpenAI is releasing a subset of datasets, reference code, and the g-mean 2 metric for evaluating chain-of-thought monitorability. The release includes most datasets from its monitorability suite, while some evaluations relying on private or restricted data were omitted. The company says it will keep reporting monitorability results in future frontier reasoning model system cards.

AI…sandbox get now shows the active runtime polic 🔒 supervisor seccomp improvements and HTTP normalization Update sandbox policy without restarting the runtime.

AI…fixes, docs refresh, and test stability libkrun lands as a lightweight VM backend, a second compute path for agents

AI…gateway without building from source.

AIOpenAI released Privacy Filter, a bidirectional token-classification model that detects and masks personally identifiable information in text under the Apache 2.0 license. The model has 1.5B total parameters with 50M active, supports a 128,000-token context window, and can run in a web browser or on a laptop. Users can fine-tune it and adjust precision/recall tradeoffs through preset operating points.

AIBAAI has released ClawKeeper v1.0, an open-source security framework for AI agents built around OpenClaw. It combines Skill-based command-level policies, Plugin-based runtime monitoring, and an independent Watcher that intervenes against high-risk operations such as prompt injections, key leaks, rogue commands, and remote code execution, even if the agent is compromised.

AIAll the code was written as matmul + epilogue so once the mainloop was implemented for Blackwell consumer cards, all the fancy symmetric matmul just works and get speed-of-light

AIBlack Forest Labs released FLUX.2 Small Decoder, a distilled VAE decoder that works as a drop-in replacement for the standard FLUX.2 decoder on Hugging Face. It decodes about 1.4x faster and uses about 1.4x less VRAM at decode time, with ~28M decoder parameters versus ~50M in the full decoder and minimal quality loss. It is available under the Apache 2.0 license and is compatible with FLUX.2-klein-4B, FLUX.2-klein-9B, FLUX.2-klein-9b-kv, and FLUX.2-dev.

AIJim Fan announced the open-source release of CaP-X, an agentic robotics framework in which LLM-driven agents control robot arms and humanoids through perception and actuation APIs. The release includes CaP-Gym with 187 manipulation tasks across RoboSuite, LIBERO-PRO, and BEHAVIOR, and CaP-Bench, which evaluates 12 frontier LLMs and VLMs across 8 tiers. The post also reports that a 7B open-source model rose from 20% to 72% success after 50 RL training iterations, with synthesized programs transferring to real robots.

AIMistral has released Voxtral TTS, a text-to-speech model, alongside a blog post, a playground, a technical report, and model weights on Hugging Face. The post itself contains only links and no further details about the model's capabilities.

AIDataChef, an AI4AI framework, uses reinforcement learning to automatically generate optimal data recipes for adapting LLMs. Its DataChef-32B model, using an efficient proxy reward system, matches Gemini-3-Pro in recipe generation, with its recipes surpassing expert-curated ones on AIME'25 and ClimaQA benchmarks.

AIPrismAudio is a framework that integrates reinforcement learning into video-to-audio generation, using a Chain-of-Thought planning mechanism. It builds on ThinkSound by splitting single-step reasoning into four CoT modules for semantic, temporal, aesthetic, and spatial dimensions, each with targeted reward functions. Code, model weights, and datasets are released for research and educational use under the MIT License, and commercial use requires explicit author authorization.

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. On LiveCodeBench, the model scores 55.3% pass@1 on LCBv6 versus 42.4% for its base, Qwen3-30B-A3B-Instruct-2507. The checkpoints are for reproducibility, not optimized Qwen releases, and are available under the Apple Machine Learning Research Model License.

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. On LiveCodeBench, it lifts Qwen3-4B-Thinking-2507 from 54.5% to 57.8% pass@1 on LCBv6 and from 59.6% to 63.1% pass@1 on LCBv5. The model is released as a reproducibility checkpoint under the Apple Machine Learning Research Model License, not as an optimized Qwen release.

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. The company says this approach yields strong generalization, marking a shift from small-data, weakly generalizing methods toward big-data robotic manipulation. The code has been open-sourced on GitHub.

AIBerkeley AI Research introduces SPEX, a signal-processing framework that identifies influential interactions in LLMs using far fewer ablations than exhaustive analysis. A hierarchy-based extension, ProxySPEX, matches SPEX performance with around 10x fewer ablations. The methods apply to feature, data, and model component attribution.

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. The team built CineDub-CN, described as the first large-scale Chinese television dubbing dataset, and reports that its model outperforms state-of-the-art methods on audio quality, lip-sync, timbre transition, and instruction following. Inference code and checkpoints were released on March 16, 2026, and the model runs on a consumer-grade GPU.

AIMistral AI released Leanstral 119B A6B on Hugging Face as an open-source code agent for Lean 4 proof engineering. The model uses 128 experts with 4 active per token, 6.5B activated parameters, a 256k token context window, and accepts text and image input under the Apache 2.0 license. The page also documents vLLM server deployment and Mistral Vibe integration.

Why it matters: The source specifies Leanstral's 119B MoE architecture, 256k context, Apache 2.0 license, and vLLM setup, showing how the Lean 4 proof agent could be deployed locally.

AIBlack Forest Labs has released FLUX.2 [klein] 9B-KV, a variant of FLUX.2 [klein] 9B that caches reference-image key-value pairs to speed up multi-reference editing by up to 2.5 times. The 9B flow model, which uses an 8B Qwen3 text embedder and is step-distilled to 4 inference steps, is available for non-commercial use under the FLUX Non-Commercial License and fits in about 29GB VRAM.

AIMistral Small 4 combines instruct, reasoning, and Devstral capabilities in one multimodal model with 119B total parameters, 6.5B active per token, and a 256k context window. The source reports a 40% reduction in latency-optimized end-to-end completion time and 3x more requests per second in throughput-optimized setups versus Mistral Small 3. It is released under Apache 2.0 and supports reasoning mode toggling per request.

Why it matters: The source lists architecture, context length, and mode-switching controls, letting readers compare this release's design with earlier Mistral Small models.

AINVIDIA researchers trained SONIC, a 42M-parameter transformer, to control a humanoid robot's whole body using motion tracking on over 100M mocap frames. After three days of training in simulation, the policy transferred zero-shot to the real G1 robot and reported a 100% success rate across 50 real-world motion sequences. One policy supports VR teleoperation, webcam human video, text prompts, music, and GR00T N1.5 VLA integration with 95% success on mobile tasks, and the code and checkpoints are open-sourced.

AIJim Fan announced DreamDojo, an open-source interactive world model that takes robot motor controls and generates future frames in pixels. It is pre-trained on 44K hours of human egocentric video using latent actions, then post-trained onto specific robot hardware, and a real-time version runs at 10 FPS for live teleoperation, policy evaluation, and model-based planning. The author reports a +17% real-world success gain on a fruit packing task, and weights, code, datasets, and the whitepaper are released.

AIThe model is released under the Apache 2 license, and achieves state-of-the-art transcription performance at sub-500ms latency.

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. The model integrates DeepSeek Sparse Attention to reduce deployment cost and reports strong results on reasoning, coding, and agentic benchmarks against GLM-4.7, DeepSeek-V3.2, Kimi K2.5, and several frontier models.

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.

AI☺️Models on ModelScope. @ModelScope2022

AIIntern Large Models introduces Intern-S1-Pro, a 1T-parameter MoE open-source multimodal scientific reasoning model with 1T-A22B active configuration. The post claims competitive scientific reasoning against leading closed-source models and supports vLLM and SGLang, with weights on Hugging Face and code on GitHub.

AIZ.ai has released GLM-OCR, a 0.9B-parameter multimodal OCR model for complex document understanding, under the MIT License. The model scores 94.62 on OmniDocBench V1.5 and supports deployment through vLLM, SGLang, and Ollama, with an official SDK for document parsing.

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.

AIChip Huyen built GoodAIList.com, which tracks 14K open-source AI repositories with contributions from over 145K developers. Each day it searches for new repos using 123 keywords and topics, surfaces those gaining traction, and categorizes them with AI-generated annotations that she notes are not highly accurate. The site also maps contributor locations, which she uses to find people doing interesting AI work when she travels.

AIMistral Small 4 is a 119B-parameter MoE model with 6.5B active per token and a 256k context window, combining instruct, reasoning, and Devstral-style coding in one model. It accepts text and image input, lets users set reasoning_effort per request, and is released under Apache 2.0. The model card reports a 40% latency reduction and 3x throughput versus Mistral Small 3 in its tested setups, and its benchmark chart shows reasoning scores on GPQA Diamond, MMLU Pro, AIME-style text tasks, and MMMU-Pro.

Why it matters: The model card names concrete architecture, context, and licensing details, letting readers compare its reasoning toggle and efficiency claims against other open models.

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. Its three-tier annotations at trajectory, segment, and frame levels help robots learn both what to do and how to do it. The post says integrating these annotations raised success rates on complex tasks by up to 50% for models such as π₀.

AIMistral AI released Voxtral Mini 4B Realtime 2602, a multilingual realtime speech-transcription model with 13 supported languages under the Apache 2.0 license. The model has a configurable transcription delay from 240ms to 2.4s, and it matches leading offline open-source models at a 480ms delay. The source says it is optimized for on-device deployment and is currently supported only in vLLM.

Why it matters: The source specifies the 480ms delay operating point, 4B size, Apache 2.0 license, and vLLM serving path, which matter for teams weighing realtime transcription deployment.