模型与评测

The full stack behind abundant intelligence

OpenAI CFO Sarah Friar explains how advances across chips, compute, models, and products compound to deliver more useful intelligence at greater scale and lower cost.

Jalapeño’s first results show industry-leading speed and efficiency in AI inference

Jalapeño is a custom inference chip from OpenAI that delivers faster, more power-efficient AI inference, with higher throughput and lower latency for modern models.

Granite 4.2 LLMs: How They're Built

Quantization-Aware Healing: a compressed, 4-bit model that outperforms its full-precision original

Wire It, Run It, Deploy It: AI Workflows in Gradio

Claude Desktop support with Ollama

Claude Desktop can now be configured to work with Ollama as a third-party gateway provider, making it possible to use open models in Claude.

Accelerating AI adoption with intelligent discovery in Microsoft Marketplace

Discover how Microsoft Marketplace intelligent discovery helps organizations find, compare, and adopt AI solutions faster and with confidence. The post Accelerating AI adoption with intelligent discovery in Microsoft Mar

Apodex 1.1: Scaling Agentic Intelligence for Complex Work

General-purpose language models can reason and synthesize knowledge, but complex work also requires sustained interaction with files, information sources, and executable code, together with state maintenance, failure rec

Prime Agent: A Self-Improving RLM Harness

Language models are sequential processors, but long-horizon agency requires external information and computation beyond model weights and active context. Prime Agent is an open-source harness for long-horizon evaluation

MobilePA-Bench: Benchmarking Mobile Planner Agents on Complex Real-World Tasks

As on-device LLM agents evolve into personal copilots, the mobile operating system has become a key testbed for this paradigm, making rigorous capability evaluation essential. Yet existing benchmarks fall into two camps,

Block3D: Efficient Text-to-3D Generation via Block-Wise Diffusion

While text-to-3D generation has advanced rapidly, achieving high geometric fidelity at low inference cost remains challenging. Existing text-to-3D methods either decode discrete shape tokens autoregressively or iterative

GameXpert-Bench: How Far Are Coding Agents from Expert Game Development?

Recent large language models (LLMs) can operate as coding agents that build complete games from natural language requests. Game development is especially demanding because program logic, visual and audio content, interfa

One Success Isn't Reliability: Thinkingbox, a Sandbox and Benchmark for Agents in Stateful Business Workflows

Recent agent benchmarks increasingly ground evaluation in executable environments, from code repair to web navigation, app APIs, and function calling. Yet completing consequential work beyond code requires more than prod

Task-CoEvolve: Efficient Harness Optimization via Adaptive Validation Task Selection

We present a novel approach to efficient LLM harness optimization through adaptive validation task selection. Harness optimization iteratively rewrites the harness code based on validation performance, enabling substanti

Industrial-Instruction: An End-to-End Framework for Building Instruction-Tuning and Benchmark Datasets from Industrial Technical Reports

Industrial technical reports contain high-value knowledge for maintenance, troubleshooting, and product engineering, but their heterogeneous structure (dense prose, specifications, tables) makes them difficult to index a

Mistral x HUMAIN

5 signals of trusted AI: How organizations scale AI with security, governance, and observability

Learn the five signals of trusted AI, from AI governance and security to observability and sovereignty, and discover how organizations scale AI with confidence. The post 5 signals of trusted AI: How organizations scale A

EchoWM: Open and Enterable Omnimodal World Models

We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, environmental sound, music and speech. We organize interaction around

TLive-Omni: An Omni-Modal Understanding Model for E-Commerce Live Streaming

E-commerce live streaming requires omni-modal understanding of noisy, temporally extended streams, where product facts are distributed across speech, video frames, product images, overlaid text, and user queries. We pres

Unlocking the Potential of Image Editing via Concept Scaling and Dense Supervision

Existing image editing frameworks predominantly follow the training paradigm of text-to-image diffusion models. However, extending this paradigm to image editing highlights two inherent discrepancies, specifically, the i

The Mask Is Not the Model: Auditing Prefix Invariance in Attention, State-Space, and Hybrid Sequence Models

We formalize prefix invariance: representations at position t must not depend on future inputs. We give a lightweight audit, two forward passes, no training or gradients, that localizes exactly where causality breaks. At

Towards a Densing Law for User Representation Learning at Billion-Scale Capacity

User representation learning in real-world industrial scenarios is commonly scaled by increasing user amount, behavioral sequence length and model size. However, existing methods face two challenges: (i) Bottleneck for r

RISE: Adaptive Imagination for World Action Models

World Action Models (WAMs) improve planning by incorporating future world evolution into action generation, yet existing methods allocate a fixed imagination budget to every scene. We propose RISE (Refining Imagination t

ReWorld: An Interactive World Model with Long-Horizon Memory

An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control wants a short horizon, memory wants an unbounded one. ReWorld separ