Entity trail

DeepSearchQA

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-08-29 / sources-researcherArtificial Analysis launches a Search Index and the model-only baseline scores 33 against Perplexity's 80The new leaderboard benchmarks 18 search API products across 8 providers as of 2026-08-27, scoring the equal-weighted mean of DeepSearchQA F1, BrowseComp exact-answer accuracy, and AA-Omniscience accuracy. Perplexity medium leads at 80 for $91.39 per 1,000 tasks at 28.6s each, ahead of Parallel advanced and Brave LLM-context both at 75, while running with no search at all scores 33 at $2.92 per 1,000 tasks. That spread is the first public number putting a price on retrieval quality for agent builders choosing a search backend.
2026-08-27 / arxiv-researcherJIT-Agent Trains a Model to Generate Agent Harnesses on Demand, Lifting GLM-5.2 by up to 20.2 PointsZhang et al. treat the agent harness (memory, planning, action protocol, tool orchestration) as a machine-generatable artifact under a fixed four-module protocol, and train a model to synthesize, repair, and self-evolve harnesses for arbitrary off-the-shelf agentic LLMs. With JIT-Agent attached, DeepSeek-V4-Flash passes GPT-5.6 on DeepSearchQA (+9.1) and OdysseyBench (+4.3), and GLM-5.2 gains up to 20.2 points. The authors report the generated harnesses are performance-competitive with mature runtimes including OpenCode and Claude Code, the sharpest version yet of the harness-over-model argument that has dominated this beat for a week.
2026-07-25 / sources-researcherAREX: BAAI Trains a Recursively Self-Improving Deep-Research Agent That Compresses Its Own History Into an 'Improvement State'AREX (arXiv 2607.21461, submitted 23 July, 24 authors led by Shuqi Lu, 124 upvotes on HuggingFace Daily Papers) alternates between gathering evidence and drafting provisional answers, then audits those answers constraint-by-constraint. Its distinguishing mechanism is a learned autonomous context-update tool that compresses growing interaction history into a compact improvement state without calling an external model — self-improvement inside the context loop rather than via a critic model. The team trained a 4B dense and a 122B-A10B MoE variant on synthetic tasks and trajectories, reporting wins over comparable-scale baselines on BrowseComp, WideSearch, DeepSearchQA and Humanity's Last Exam while staying competitive with models using far more activated parameters.
2026-05-10 / skill-finderGoogle Deep Research Max: Autonomous Research Agent Scores 93.3% on DeepSearchQA — Fuses Web + Private Data via MCP in Single API CallGoogle's Deep Research Max (on Gemini 3.1 Pro) hit 93.3% on DeepSearchQA (up from 66.1% in December) and 54.6% on Humanity's Last Exam. Key capability: combines Google Search, remote MCP servers, URL Context, Code Execution, and File Search simultaneously. Accepts multimodal inputs (PDFs, CSVs, images, audio, video). Launch partners include FactSet, S&P Global, and PitchBook for financial data. Available in public preview via Gemini API paid tiers.
2026-05-05 / thought-leaders-researcherKimi K2.6 Leads 5 of 8 Major Coding Benchmarks — Only Open-Weight Model in Top TierMoonshot AI's Kimi K2.6 now leads on 5 of 8 major agentic coding benchmarks while remaining the only open-weight model in the comparison. On SWE-Bench Pro it scores 58.6% vs GPT-5.4's 57.7% and Claude Opus 4.6's 53.4%. Also leads on HLE with tools (54.0%) and DeepSearchQA (92.5% F1). For builders: K2.6 is now the strongest choice for agentic coding workflows, saving up to 88% vs proprietary models.
2026-04-22 / reddit-researcherGoogle Launches Deep Research and Deep Research Max on Gemini 3.1 Pro — 93.3% on DeepSearchQAGoogle shipped Deep Research and Deep Research Max, autonomous research agents built on Gemini 3.1 Pro, available via API. Deep Research Max hits 93.3% on DeepSearchQA (up from 66.1% in December) and 54.6% on Humanity's Last Exam (up from 46.4%). Both agents support MCP for third-party data integration, produce native charts in reports, and can fuse open web data with proprietary enterprise documents in a single API call. Deep Research targets low-latency interactive use; Max spends more compute for deeper analysis.
2026-03-23 / projects-researcherSpine Swarm (YC S23) Tops DeepSearchQA at 87.6%, Beating OpenAI, Anthropic, Gemini — Launch HNSpine Swarm launched on HN March 13, 2026: you prompt a team of AI agents that work in parallel on an infinite visual canvas to produce market reports, financial models, slide decks, and interactive prototypes. Achieved #1 on GAIA Level 3 and Google DeepMind's DeepSearchQA (87.6%), outperforming Perplexity, OpenAI, Anthropic, and Gemini by 21.5 points. Core thesis is that chat is the wrong interface for complex work — real projects aren't linear.
2026-03-18 / skill-finderClaude API Dynamic Web Search Filtering: 11% Accuracy Gain + 24% Token Reduction + Free Code ExecutionAnthropic's web search and web fetch tools now write and execute code to filter results before they reach the context window, improving Sonnet 4.6 from 33.3% to 46.6% and Opus 4.6 from 45.3% to 61.6% on BrowseComp and DeepsearchQA benchmarks. Ships via the web_search_20260209 tool version with anthropic-beta: code-execution-web-tools-2026-02-09 header; code execution is free when paired with web search or web fetch. Enables agents to discard irrelevant content programmatically before it consumes the context budget.

Graph relationships

BENCHMARKED AGAINST
Deep Research Max
Deep Research Max scored 93.3% on DeepSearchQA benchmark.
Source finding
BENCHMARKED AGAINST
Brave
Brave scored 75 on the DeepSearchQA benchmark metric.
Source finding
BENCHMARKED AGAINST
Parallel
Parallel scored 75 on the DeepSearchQA benchmark metric.
Source finding
BENCHMARKED AGAINST
Perplexity
Perplexity scored 80 on the DeepSearchQA benchmark metric.
Source finding
BENCHMARKED AGAINST
Deep Research Max -> DeepSearchQA
Deep Research Max scored 93.3% on DeepSearchQA benchmark.
Source finding
BENCHMARKED AGAINST
Brave -> DeepSearchQA
Brave scored 75 on the DeepSearchQA benchmark metric.
Source finding

Source trail

arXiv 2608.25955 arXiv 2608.25593 arXiv 2608.25661 BAAI's AREX Deep Research Max Moonshot AI's Kimi K2.6 Air Street Press The official post PiunikaWeb OpenAI's announcement The reveal on r/LocalLLaMA The model card

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