Tagged articles

agent performance

6 articles · Page 1 of 1
SuanNi
SuanNi
Aug 13, 2026 · Artificial Intelligence

DeepSeek V4 Pro vs. Grok 4.6: How New LLMs Challenge Top Closed‑Source Models

The newly released DeepSeek V4 Pro and Elon Musk’s Grok 4.6 deliver performance and cost metrics that rival or surpass leading closed‑source LLMs, with DeepSeek achieving up to 29‑fold cheaper token output and top scores on Agent, CyberGym, AutomationBench, Terminal‑Bench, and professional legal benchmarks, while Grok 4.6 matches GPT‑5.6 on the AA Intelligence Index and leads in workplace knowledge tests.

AIDeepSeekGrok
0 likes · 6 min read
DeepSeek V4 Pro vs. Grok 4.6: How New LLMs Challenge Top Closed‑Source Models
Machine Heart
Machine Heart
Aug 12, 2026 · Artificial Intelligence

DeepSeek V4 Pro (0813) Launches with Claude-Level Agent Performance

DeepSeek has officially released its V4 Pro large language model, designated DeepSeek‑V4‑Pro‑0813, with unchanged API pricing, a noticeable shift in chain‑of‑thought behavior, and benchmark results that put its agent capabilities on par with top models like Claude Fable 5, while recent V4 Flash users report performance drops and potential price hikes.

AI benchmarkingClaudeDeepSeek
0 likes · 3 min read
DeepSeek V4 Pro (0813) Launches with Claude-Level Agent Performance
SuanNi
SuanNi
Jun 2, 2026 · Artificial Intelligence

Why the Best AI Scores Only 45.9% on JobBench’s ‘Dirty Work’ Benchmark

Washington University’s JobBench benchmark, built on a 1,500‑person Workbank survey and 130 real‑world tasks, measures how well AI agents can handle the chores professionals most want to delegate, revealing that even the strongest model, Claude Opus 4.7 + Claude Code, achieves just 45.9% overall, far below human‑level performance.

AI benchmarkJobBenchLLM evaluation
0 likes · 13 min read
Why the Best AI Scores Only 45.9% on JobBench’s ‘Dirty Work’ Benchmark
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 15, 2026 · Artificial Intelligence

ClawMark: A Living‑World Benchmark for Multi‑Turn, Multi‑Day, Multimodal Coworker Agents

The ClawMark benchmark introduces 100 multi‑turn, multi‑day tasks across 13 professional scenarios and five stateful sandbox services, evaluating seven cutting‑edge agent systems with a top weighted score of 75.8 but only a 20% strict success rate, highlighting the difficulty of end‑to‑end collaborative agent performance.

LLMagent performancebenchmark
0 likes · 4 min read
ClawMark: A Living‑World Benchmark for Multi‑Turn, Multi‑Day, Multimodal Coworker Agents
Baidu Geek Talk
Baidu Geek Talk
Apr 22, 2026 · Artificial Intelligence

How to Quantify AI Skill Quality with an 8‑Dimension Evaluation Framework

This article introduces an eight‑dimensional, weighted scoring system for evaluating AI Skills, explains each metric, demonstrates the framework on real‑world Skills, compares similar Skills, and shows how multi‑model cross‑validation and four execution strategies improve assessment reliability.

AI skill evaluationMetadata Qualityagent performance
0 likes · 15 min read
How to Quantify AI Skill Quality with an 8‑Dimension Evaluation Framework
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Mar 19, 2026 · Artificial Intelligence

From Language Modeling to World Modeling: Limits of Large Language Models

Speaker Li Yixia from Southern University of Science and Technology presents a talk on using large language models as textual world models, defining a three‑layer evaluation framework and showing through experiments that fine‑tuned models improve next‑state prediction and agent performance, yet face limits tied to behavior coverage and environment complexity.

Large Language ModelsReinforcement LearningWorld Modeling
0 likes · 4 min read
From Language Modeling to World Modeling: Limits of Large Language Models