All AI news

AILiquid AI announced d1, its first decision model, which it says is the first to outperform Jev on Hugging Face's Decision Index. The company claims d1 wins on multilingual evals, resists prompt injection better, handles longer inputs more effectively, and is built for fast, structured decision-making in software environments. It is available via the Liquid API at console.liquid.ai, with OpenRouter availability coming soon.

AIOpenAI reports that GPT-6.1 Sol shows major alignment improvements over GPT-6 Sol in its evaluations, moving closer to GPT-6 Astra. The model is more transparent about its limitations and more reliable at respecting user intent and safety constraints.

AIModelScope announced IQuest-Q1, a 320B MoE model with 15B active parameters and a 512K context window for agentic coding. The post reports scores of 84.5 on CyberGym, 83.2 on Terminal-Bench 2.1, 64.6 on DeepSWE v1.1, and 63.0 on NL2Repo, and says weights are released under the IQuest-Q1 License.

AIShanghai AI Laboratory's Intern-Decision family of 0.8B, 2B, and 4B multimodal models averages 79.38, 84.68, and 90.02 across seven decision benchmarks. Intern-Decision-4B scores 88.74, surpassing Jev while achieving better probability calibration. Reported mean latency is 33.98, 33.28, and 44.16 ms, versus 109.70 ms for Jev in the same local HF setup.

AIAudio8 ASR Infinite transcribes Chinese and English audio of unlimited length using a rolling KV Cache that avoids accumulated drift. At a 480 ms delay, it reports 1.75 CER on AISHELL-1, 2.89 on AISHELL-4, and 3.04/6.81 WER on LibriSpeech test-clean/test-other. The preview release is under Apache 2.0, with deployment through an adapted vLLM stack.

AIAnthropic's Cat Wu says Claude Sonnet 5.5 lets Claude Code users complete about 30% more tasks than with Sonnet 5. The model needs fewer tokens for the same work, and in a leaf-raking tool-call demo it finished 24 seconds faster using 6K fewer tokens.

Why it matters: The post gives a measured Claude Code task-completion gain and a token-use example, showing what the model upgrade means for a coding agent workflow.

AIAnthropic's Claude Sonnet 5.5, the second model in the Claude 5.5 family, is shown fixing a bug in Claude Code. Boris Cherny says it runs 30% faster and uses 30% less usage, and Anthropic's announcement says it runs over 30% faster and costs up to 30% less for most work.

AIAnthropic launched Sonnet 5.5, which the post says is smarter and more tasteful than Sonnet 5. It is positioned for work that does not need the extra capability of Opus or Fable.

AIJina-OCR-v1, a 3.4B-parameter MoE model that activates 570M parameters per token, converts entire document pages into structured Markdown at 2.57 pages per second. It scores 91.14 on OmniDocBench v1.6 and 83.4 on olmOCR-Bench, 7.4 points above DeepSeek-OCR on the latter, and delivers the highest throughput among 14 evaluated systems at concurrency 32. The model is released under CC BY-NC 4.0, so commercial use requires permission.

AIMeituan's LongCat team has released LongCat-2.5-Preview, a natively multimodal model with 1.6T total parameters, about 48B active, and a 1M-token context window. The model is built for long-horizon tasks spanning terminals, browsers, GUIs, spreadsheets, and design tools. It is available now through an API on the LongCat platform and a chat interface.

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.

AIOdyssey introduced Agora-2, its next-generation multi-agent world model, which supports up to 20 humans and agents interacting in a shared environment simulated in real time. A multiplayer research preview is available to try now.

AIGoogle's Philipp Schmid announced Gemini 3.8 Flash, recommending Gemini for multimodal understanding. A quoted post by Spencer Schiff reported that frontier models struggled to match correct names to people in a drawing, offering a visual test for future models.

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.

AIBlack Forest Labs says FLUX 3 Action can control a simulated drone to carry out a specific requested action. The post offers no further details on benchmarks, availability, or implementation.

AIBlack Forest Labs says FLUX 3 Action takes recent camera frames, the system's current state, and a task description to return the next 32 actions. The model also predicts how the scene will change, and runs a continuous observe-plan-act-adjust loop. It can recover from its own mistakes, according to the company.

AIBlack Forest Labs says FLUX 3 Action builds on the same image, video, and audio pretraining as FLUX 3 but uses a smaller architecture. The company attributes this smaller size to more efficient representations learned through its Self-Flow research. During midtraining, the model was trained to predict actions and future frames together.

AIBlack Forest Labs says its FLUX 3 Action, a single-step 7B checkpoint, outperforms every other open policy on RoboLab. It processes each second of robot motion 1.45× to 1.66× faster than Pi0.5, and uses a 2.13-second action horizon versus Pi0.5's 1 second. The company adds that its guidance-distilled checkpoint raises the state-of-the-art RoboLab success rate while running 2.85× to 3.15× faster than the previous leading open WAM.

AIBlack Forest Labs says FLUX 3 Action is an open-weights 7B world action model that ranks first on the RoboLab benchmark. The company says it outperforms the previous best open model by 6.1 percentage points while using 56% fewer parameters and running up to 3.95x faster. The model predicts video and actions together, and the company is releasing the weights, code, fine-tuning recipe, benchmarks, and examples. It also integrated the model into Hugging Face's LeRobot with NVIDIA, with edge deployment on NVIDIA Jetson.

Why it matters: The release pairs benchmark results with the trade-off it claims to remove between world action model performance and VLA speed, which is useful context for robotics teams weighing open models.

AIMicrosoft AI reports its image model rose from 864 to 1147 Elo in nine months, a gain of 377 points per year. The company says that pace is 1.6 times the next-fastest climb on the leaderboard. The post does not name the model.