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#Open source/Repo

Sep 26

Sep 26Sat
  1. Alexander DoriaAI score38

    Xiaomi open-sources 989 RL environments used for a 9B MiMo model

    AIAlexander Doria reports that the released set is a smaller selection of 989 environments for RL training a 9B distilled model, not the full MiMo. Rewards are not self-contained: the general part requires setting up a judge, and webdev relies on its own grader service and VLM. The most important content is in the general/envs directory and Docker setup rather than the Hugging Face dataset, offering a solid mix of real and simulated documents.

  2. InternLM (Shanghai AI Lab) · new models on Hugging FaceAI score45

    Intern-Decision-4B: Multimodal structured decision model from Qwen3.5-4B

    AIShanghai AI Lab's InternLM released Intern-Decision-4B, a multimodal structured decision model fine-tuned from Qwen3.5-4B, which returns answer distributions for multiple questions in one forward pass. On its benchmark table it scores an average of 90.02 with a Brier score of 0.347 and an ECE of 0.065, and per-query latency averages 44.16 ms on a single RTX 4090. The model is available with a Python DecisionEngine inference interface.

  3. InternLM (Shanghai AI Lab) · new models on Hugging FaceAI score46

    Intern-Decision-0.8B: InternLM's structured decision model on Hugging Face

    AIInternLM released Intern-Decision-0.8B, a multimodal structured decision model fine-tuned from Qwen3.5-0.8B that scores answers to multiple questions in one forward pass. The model reports a 79.38 average score and a 33.98 ms mean latency on a single RTX 4090, with 0.8B, 2B, and 4B sizes available. It is accessed through a Python DecisionEngine API that returns calibrated probabilities rather than generating free-form text.

Sep 25

Sep 25Fri

Sep 24

Sep 24Thu
  1. ModelScopeAI score23

    NeoHorse-Jev-4B open model turns app states into structured decisions

    AIModelScope has released NeoHorse-Jev-4B, a compact open model that converts application states into structured decisions and probabilities. It scores 77.70 across six text decision benchmark groups, ranking first among four open-weight models with complete results in the comparison. Its prefill-only inference supports Choice, Noul, and Score primitives, accepts text or a single image with text, and is available under Apache 2.0 for deployment via vLLM, SGLang, Python, CLI, or HTTP.

  2. Lewis TunstallAI score42

    Hugging Face releases over 5,000 RL environments for data science tasks

    AIHugging Face released SmolDataEnvs, more than 5,000 open-source RL environments aimed at real-world data science tasks. They target the gap between simple educational games and frontier-level benchmarks, especially for improving coding in models under 10B parameters. The environments are designed as a testbed for developing new RL methods such as GRPO or OPSD.

  3. Baseten BlogAI score44

    LangSmith Fine-Tuning Trains Open Models on Agent Traces via Baseten Loops

    AILangChain launched LangSmith Fine-Tuning, which lets users fine-tune open models on their LangSmith agent traces using the open-source smithtune CLI. Training runs on Baseten Loops in the user's own workspace, and smithtune deploy places the evaluated checkpoint on a Baseten Dedicated Inference deployment. Loops is in early access, so users may need to request access for their workspace.

  4. GitHub Blog · AI & MLAI score66

    GitHub Security Lab shows an LLM agent running AI-driven fuzzing for C/C++ projects

    AIGitHub Security Lab describes the Fuzzing Taskflow, an LLM agent pipeline that identifies entrypoints, writes harnesses, runs AFL++, reads coverage reports, and triages crashes for C/C++ repositories. The agent makes decisions while MCP tools handle execution, and state is stored in a SQLite database. The post also warns that the taskflow runs AFL and build commands directly on the host, so it should be used only in disposable environments without elevated privileges.

    Why it matters: The post explains how an LLM agent automates fuzzing steps like harness writing, coverage gap chasing, and crash triage, with a runnable workflow and design tradeoffs.

  5. vLLMAI score34

    vLLM and RL-Kernel achieve bit-exact logprob match on AMD MI300X

    AIThe RLKernel team integrated RL-Align/RL-Kernel with vllm-project/vime, and a 200-step Qwen3-8B GRPO run on 8× AMD MI300X recorded zero logprob mismatches between Megatron training and vLLM rollout. The strict path aligns reduction order, intermediate precision, rounding points, and math primitives across both sides to achieve bit-for-bit matching on ROCm.

  6. OpenBMBAI score34

    FIT-GGUF enables size-targeted mixed-precision quantization of MiniCPM5-2B

    AIDeveloper @Scorp1o_117 used FIT-GGUF to build four MiniCPM5-2B GGUF variants, ranging from about 1.14 GiB to 1.46 GiB, tuned to target file sizes or fidelity tiers. Instead of fixed presets, FIT-GGUF allocates precision tensor by tensor, with Quality, Balanced, Compact, and Mini options, and its generated files matched predicted sizes. Builds are evaluated with KL Divergence and Same-top metrics and are available on Hugging Face.

  7. ModelScopeAI score38

    Qwen-Image-2.1-Fun-Controlnet-Union adds eight controls and inpainting

    AIModelScope released Qwen-Image-2.1-Fun-Controlnet-Union, a single checkpoint adding eight structural controls, including Canny, Depth, Pose, and Scribble, plus inpainting to Qwen-Image 2.1. Control and inpainting share one branch with 16 injection points across every second Transformer block, keeping the base model frozen and requiring no checkpoint switching. It runs at guidance scale 1.0 with CFG-distilled sampling and prefix KV caching, and is available under the Qwen Research License with base Qwen-Image 2.1 weights required.

  8. inclusionAI (Ant Ling) · new models on Hugging FaceAI score22

    inclusionAI Publishes Training-Content Summaries for Ling and Ring Models

    AIinclusionAI has published public training-content summaries on Hugging Face for its Ling and Ring model versions, including Ling-2.0, Ling-2.5, Ling-2.6-1T, Ling-3.0, Ring-2.0, Ring-2.5-1T, and Ring-2.6-1T. The documents, organized under the template associated with Article 53(1)(d) of Regulation (EU) 2024/1689, contain documentation only, not model weights or training datasets. Each summary covers only the model versions it names.

Sep 23

Sep 23Wed
  1. Midjourney UpdatesAI score31

    Midjourney Alpha changelog adds style previews, default parameters, and a new Create feed

    AIMidjourney's alpha site now lets users preview their current prompt across styles with "Live previews" in the Styles sidebar and save prompt-bar settings as defaults via Settings → Advanced → Your defaults. The Create feed received a full-width masonry redesign with hover-based prompts and buttons, and Korean is now live for all users on midjourney.com.

  2. Microsoft ResearchAI score60

    Microsoft Research shows offloading robot AI inference improves performance and battery life

    AIMicrosoft Research reports that running physical AI inference on onboard GPUs can limit robot performance and battery life, while offloading inference to edge or cloud GPUs improved results in mobile manipulation tests. In its evaluation, smaller onboard GPUs slowed mapping and planning by up to 383% compared with an A100, and large onboard GPUs such as Jetson Thor drained robot batteries by up to 160%.

    Why it matters: The study measures how offloading robot inference to edge or cloud GPUs changes task success, battery life, and model size, offering evidence for infrastructure design.

  3. Mike KnoopAI score57

    Tufa Labs reaches 83.06% on ARC-AGI-2, 2% short of the grand prize

    AIMike Knoop says the top ARC Prize 2026 ARC-AGI-2 score of 83.06% by Tufa Labs is only 2% short of the 85% grand prize threshold. The challenge runs under strict Kaggle compute limits with no internet access, and the winning solution is set to be open sourced. The image shows the leaderboard with RabbitHole at 76.94%, nvbanana at 74.17%, Yi-Chia Chen at 55.14%, and Kha Vo at 37.50%.

  4. ModelScopeAI score44

    NVIDIA releases Nemotron 3 Diarization for live speaker attribution

    AINVIDIA's Nemotron 3 Diarization is now available on ModelScope, labeling speakers and timestamps in streaming audio for up to eight speaker slots per conversation. The 99.2M-parameter model uses an end-to-end streaming architecture built on NVIDIA's Streaming Sortformer, running on Ampere, Hopper, and Blackwell GPUs via NeMo Speech C++. It is designed to pair with existing ASR systems such as Nemotron ASR, Parakeet, Canary, or Whisper to produce speaker-attributed transcripts.

  5. QwenAI score60

    Qwen Intelligence launches three mobile agents and opens its benchmark suite

    AIAlibaba's Qwen launched Qwen Intelligence with three mobile agents: a Mobile Planner Agent, a Mobile-Use Agent, and a Mobile Creative Agent. The post reports benchmark results including MobileWorld 82.1, MobileWorld-Real 92.2, and AndroidDaily 97.2, plus a 90% end-to-end success rate, and says the MobilePA-Bench, MobileWorld, MobileWorld-Real, and MobileWorld-Safety benchmarks are open.

  6. ModelScopeAI score62

    Xiaomi MiMo-V2.6 open-sourced as a multimodal agent model family under MIT License

    AIXiaomi has released MiMo-V2.6 as an open model family under the MIT License, designed for large-scale reinforcement learning. MiMo-V2.6-Pro scores 46 on the Artificial Analysis Intelligence Index, with 71.9 on DeepSWE v1.1, 89.9 on Terminal-Bench 2.1, and 82.0 on OSWorld-Verified. The 1.02T-parameter MoE activates 42B parameters and supports text, image, video, and audio input with a 1M-token context.

Sep 22

Sep 22Tue
  1. StepFunAI score43

    StepFun open-sources onPanda for token-level LLM annotation and inspection

    AIStepFun has open-sourced onPanda, a tool used internally for LLM data annotation and model inspection, letting users correct tokens and let models continue. The company reports a 52% lower median annotation time versus manual post-editing, with SFT and preference data combined in one workflow. It also supports token probability and top-k inspection, token-by-token decoding control, and browser-based testing across SVG generation, web development, and agent tasks.

  2. StepFunAI score52

    StepFun releases Step Code v0.1.0 as an open-source coding CLI

    AIStepFun has released Step Code v0.1.0, an open-source command-line tool under the MIT License that covers reading and editing code, running tests, and shipping from one CLI. The post reports 80.9% on Terminal-Bench 2.1 and 73.3% on Multi-Frame, a 150-task long-horizon benchmark from StepFun. It also includes one-command static site publishing with StepPage and links the GitHub repository.

  3. OpenBMBAI score59

    VoxWeft runs real-time interpretation locally on Apple Silicon using VoxCPM2

    AIOpenBMB highlights VoxWeft, an open-source simultaneous interpretation system for Apple Silicon built by developer @HenryZ30734018 on an MLX implementation of VoxCPM2. The system turns live speech into translated speech on-device, with first audio streaming in about 170 ms on an M5 MacBook. VoxCPM2 generates speech in 30 languages, supports direct language-pair interpretation, and clones a target voice from about 5 seconds of reference audio.