最新模型

新模型、開放權重、多模態、語音、影像與模型架構。

代理工具

Model Main Effects Fall Below 3% Across Three Agent Benchmarks, as DDR Recasts Leaderboards as a Deployment Reliability Problem

A new study uses generalizability theory to decompose results from TheAgentCompany, τ²-bench, and AppWorld, finding that agent–task interactions far outweigh average differences between agents. The authors propose the DDR reporting framework, which requires model-selection decisions to disclose task difficulty, holdout validation, cost, and required sample size.

最新模型

Qwen3.8 Makes 2.4T-Parameter Max-Class Weights Available for the First Time, Activating 95B per Token

Alibaba’s Qwen team has released Qwen3.8-2.4T-A95B, featuring 512 experts and a hybrid of linear and standard attention, with support for contexts of up to approximately 1.01 million tokens. The model offers adjustable reasoning depth, but accepts text only and cannot disable thinking mode, making its practical deployment requirements far higher than those of typical open-weight models.

最新模型

Rankings Reverse for the Same Models as Token Limits Change, Four-Model Test Records 56,476 Inferences

A new study increased the generation limit for four open-weight models from 64 to 4,096 tokens and found that the leading model changed on all three reasoning benchmarks. Even after truncated outputs were excluded, 3% to 19% of questions changed from correct to incorrect as the budget increased, showing that a single token setting is insufficient for deployment decisions.

代理工具

Bench2Robust Injects Nine Types of Tool Failures; Performance Regresses in 69 of 70 Agent Evaluations

An Amazon research team transformed existing tool-use benchmarks into fault environments in which agents can be instructed to retry, switch tools, or stop. After structured recovery information was added to Qwen3-4B, its pass rate on disrupted retail tasks increased by as much as 16.8 percentage points, but the system has yet to truly validate correct abstention on unsolvable tasks.