baidubce

baidubce / qianfan-deepresearch-bench

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Baidu Qianfan Deep Research

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100% credibility
Found Feb 02, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

This repository presents official benchmark results from Baidu's Qianfan team, showcasing top rankings for their Qianfan-DeepResearch models on the DeepResearch Bench across various research evaluation dimensions.

How It Works

1
🔍 Hear about AI research benchmarks

You come across discussions on the best AI tools for deep research tasks and find the DeepResearch Bench leaderboard.

2
🏠 Visit Baidu's results page

You head to Baidu Qianfan's special page sharing their official benchmark scores.

3
🏆 Spot Qianfan at the top

You see the exciting table where Qianfan-DeepResearch Pro and Qianfan-DeepResearch rank first and second overall, beating many big names.

4
📊 Check scores across categories

You review the breakdown of scores in comprehensiveness, insight, following instructions, and readability.

5
📄 Explore task details

You look at results for 100 tasks across 22 fields and read the detailed reports.

✅ Feel confident in top performer

You now know Qianfan-DeepResearch excels in deep research, ready to try it out.

Sign up to see the full architecture

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Star Growth

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AI-Generated Review

What is qianfan-deepresearch-bench?

This Baidu AI Cloud Qianfan repo publishes official benchmark results for Qianfan-DeepResearch models on the DeepResearch Bench, a test for deep research agents across 100 tasks in 22 fields. It ranks Qianfan-DeepResearch Pro at #1 (54.48 overall) and the base model at #2 (53.07), topping metrics like insight and comprehensiveness over rivals like Tavily and OpenAI DeepResearch. Developers get leaderboard submissions, raw scores, and reports via Baidu Qianfan platform integration, all in English and Chinese READMEs—no code to run, just data to validate Baidu Ernie-powered research tools.

Why is it gaining traction?

Baidu Qianfan DeepResearch crushes the leaderboard with median scores from multiple runs, proving stronger readability and instruction-following than LangChain setups or Gemini/Claude baselines. On Baidu AI GitHub, it hooks devs eyeing Qianfan API or LangChain Baidu Qianfan combos for real-world research automation. The transparent †-marked results and Hugging Face leaderboard link build trust in 百度千帆's edge without hype.

Who should use this?

AI researchers benchmarking deep research agents before picking Baidu Cloud Qianfan VL or API. Teams building on Baidu Qianfan platform who need proof it outperforms Salesforce AIR or ThinkDepth.ai on diverse tasks. Devs forking Baidu AI GitHub projects like Apollo or netdisk tools, now validating Qianfan for smarter querying.

Verdict

Skip unless you're deep into Baidu Qianfan—21 stars and 1.0% credibility signal early immaturity, though bilingual docs and linked data make it a fast credibility check. Worth a peek for 百度千帆 fans chasing bench-topping research agents.

(178 words)

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