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under medium-utilization production workloads. Voice in the call center. MAI-Voice-2-Flash now powers Dynamics 365 Contact Center, the enterprise platform for building call center agents used by customers like T-Mobile and EasyJet, bringing our most expressive, natural sounding speech to brand defining conversations while reducing GPU costs up to 89%. MAI-Voice-2-Flash integrated in Azure Voice Live. Customers can quickly build voice agents in Voice Live, powered by MAI‑Voice‑2‑Flash’s natural,

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r models, we pushed performance up by as much as 7.9 points. We are now beating leading models like Fable 5 in complex coding and reasoning tasks, without even having Fable in our agent pool. Collective intelligence is the future! Fugu-Ultra v1.1: The Frontier Keeps Moving Fugu-Ultra is now upgraded to incorporate the latest frontier models. Our latest Fugu-Ultra v1.1 delivers stronger performance across every benchmark we track. This orchestration upgrade resulted in gains of up to 7.9 points o

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on for controlled transitions between defined moments; Multilingual dialogue; A broad range of visual styles and aspect ratios, extending far beyond conventional cinematic output; Agentic chaining of individual clips into longer, multi-shot sequences; High style diversity -- FLUX 3 Video easily handles ranges of styles from candid camcorder footage to animation and cinematics; Strong typography generation and animated designs For the preliminary analysis below, we generated 10-second text-to-vid

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Flynn Share Google has invested in cybersecurity for years, pioneering automated vulnerability discovery to secure the world’s codebases. Tools like CodeMender , our code security agent, can automatically find and fix critical software vulnerabilities. But as AI agents become more capable at finding vulnerabilities faster than defenders can fix them, addressing this global threat requires a highly capable, affordable, and scalable approach. Today, we’re expanding our longtime efforts to better p

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Jul 21, 2026 Our newest Gemini models deliver the efficiency, latency, and reliability to build AI agents at scale. Tulsee Doshi Senior Director, Product Management, on behalf of the Gemini team Developers and customers building production AI agents need higher token efficiency, lower latency, and more reliable performance. Our Flash series of models is built to meet the sweet spot of efficiency and quality to enable scaling agentic workflows. Building on Gemini 3.5 Flash, we’re introducing new

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hmarks, matching cyber-focused frontier models like GPT-5.5-Cyber and Mythos Preview. Together, these benchmarks test the core pillars of enterprise defense: CyberGym evaluates an agent’s ability to analyze complex codebases to verify real-world vulnerabilities, while CTI-REALM measures its capacity to translate raw threat intelligence reports into working detection rules. Like our original Fugu orchestration model, Fugu-Cyber is a multi-agent system that behaves like a single model. You send a

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Intelligence Conference in Shanghai where Chinese President Xi Jinping called for greater open-source collaboration. What makes K3 an unusual release though is not the coding and agentic performance, nor the efficiency optimization in training and inference. It’s the positioning. In my opinion K3 is an ambitious, even risky attempt to get rid of the old stereotype of Chinese models as a cheap alternative. Instead it is a high-end, premium model built to fight the world’s best proprietary fronti

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Today, we're launching Grok 4.5 , SpaceXAI's smartest model built to excel at coding, agentic tasks, and knowledge work. It's our strongest model ever and was trained alongside Cursor . Real-world engineering excellence Grok 4.5 was trained on datasets spanning knowledge in coding, science, engineering, and math. With both intelligent and efficient reasoning, Grok 4.5 excels at real engineering tasks and exceeds comparable leading models at these tasks. 0% 20% 40% 60% DeepSWE score (pass@1) 66.1

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hatting with the model, and set it up with your favorite MCPs, pass in images or files conveniently and more! Llama cpp also ships with a built-in UI that supports tools, mcp, and agentic workloads. Checkout Inkling running at 1-bit precision in the llama app: Inkling GGUFs are also runnable in Unsloth Studio with dynamic 1-bit GGUFs which retain 74.2% of top-1% accuracy whilst being 86% smaller. Use Cases Agentic coding with Pi Pi is a minimal coding agent harness you can use with different lan

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to adjust how much reasoning the model applies based on the needs of each task. Its post-training also spans a wide range of capabilities, including scientific reasoning, coding, agentic workflows, forecasting, and calibrated prediction. Under the hood, Inkling introduces several architectural innovations beyond a conventional decoder-only Transformer, including query-conditioned relative attention, short causal convolutions throughout the model, and a mixture-of-experts architecture with a sha

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a ‘post-training ceiling’ and suggest that RL can push capabilities much further than previously believed. At Cognition, we have been formulating and refining principles for good agentic software engineering both in evaluation, with FrontierCode1,2, and now in training, with SWE-1.7. Our model is particularly optimized for longer-horizon asynchronous tasks, an important component of high-quality software engineering. SWE-1.7 is available today in Devin (Web, Desktop, and CLI) via Cerebras at 10

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, so we are confident that more training and more experiments will continue to push this number up. What's Next Robostral Navigate is only the first step toward a unified embodied agent. We believe navigation is a foundational capability for general-purpose robotics. By combining large-scale simulation, efficient training, and strong grounding priors, Robostral Navigate demonstrates that state-of-the-art embodied navigation can be achieved with a compact model and a single RGB camera. Start your

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Claude Sonnet 5 is built to be the most agentic Sonnet model yet. It can make plans, use tools like browsers and terminals, and run autonomously at a level that, just a few months ago, required larger and more expensive models. For many developers, the agentic AI era began with Sonnet-class models: Claude Sonnet 3.5, 3.6, and 3.7 were the first models that showed impressive skills in coding and tool use. More recently, though, the clearest gains in agentic capabilities have been in our Opus-clas

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On this page Today, we're releasing LFM2.5-230M, our smallest model yet. It’s a fast, lightweight foundation for developers to fine-tune and deploy in agentic workflows. Built on the LFM2 architecture, it delivers exceptionally fast inference and runs everywhere, from cloud GPUs to low-cost CPUs (213 tok/s decode speed on Galaxy S25 Ultra, 42 tok/s on a Raspberry Pi 5). Despite its small size, it’s surprisingly capable at tool use and data extraction tasks. The base (LFM2.5-230M-Base) and post-t

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osted deployments. It outperforms leading OCR systems in human evaluations and benchmarks while offering cost-efficient, high-throughput processing for enterprise search, RAG, and agentic workflows. Available via API or Document AI, it provides structured outputs for custom pipelines or no-code applications, with self-hosting options for data privacy. Today, we're releasing Mistral OCR 4, featuring bounding boxes, block classification, and inline confidence scores alongside extracted text. The m

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We have released Fugu Max, optimized for cost/performance at the Pareto Frontier. We are excited to introduce Sakana Fugu, a new product from Sakana AI that delivers a full multi-agent orchestration system as a single foundation model. Fugu dynamically orchestrates the world’s best models to tackle complex, multi-step tasks, accessible through a single model API. The result is multi-agent intelligence delivering the very best frontier-level performance without any single-vendor dependency or th

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nonical space, enabling cross-embodiment training at scale. World co-trains 20+ embodiments via a natural-language action interface under one world model. Together, they enable an agentic system where general intelligence translates directly into physical action. The Qwen family of multimodal foundation models has made remarkable progress in understanding the physical world. Qwen-VL can parse complex spatial relationships, identify objects in cluttered scenes, follow multi-step visual instructio

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rolling out new features over the next few days to improve your creative workflow: Projects Organize your work into Projects that appear on the left sidebar. 0:00 / 0:00 Multiple agents Kick off multiple agents in parallel on your projects. Instead of waiting for one generation to finish before starting the next, you can run several prompts at once and let them work for you. 0:00 / 0:00 Search Find any image or video you've made by searching your library — no more scrolling to track down that o

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autonomy and reliability that exceeded previous benchmarks. But what excites us most is the direction it points: a future where developers can hand increasingly ambitious work to agents and trust the results across the software lifecycle.Mario Rodriguez Chief Product Officer These are the strongest results of any Claude model we've had the opportunity to test. Claude Fable 5 is a clear step forward on agentic coding and prototyping.Matt Colyer Director of Product, Developers Claude Fable 5's re

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Today we're launching North Mini Code open-source. A mixture-of-experts (MoE) model, North Mini Code is Cohere's first agentic coding model, and the inaugural member of our next generation of powerful models. At 30B total parameters with just 3B active, North Mini Code delivers strong software development performance without demanding extensive hardware to match. Efficient by design, it's built to run where you need it. Freely available under an Apache 2.0 license, North Mini Code advances Coher

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