Forward Future Tools Library
DeepResearch
Tongyi DeepResearch is an open-source Alibaba agentic language model for long-horizon information-seeking tasks, with local deployment and online demos for researchers and developers.
Try DeepResearch →
github.com·Free
›What is DeepResearch?
Tongyi DeepResearch is an open-source agentic language model from Tongyi Lab, built for long-horizon, deep information-seeking tasks. It has 30.5 billion total parameters, with 3.3 billion activated per token. The repository includes agent, web, inference, and evaluation components, plus links to ModelScope, Hugging Face, and Bailian deployments.
›What are the pros and cons of DeepResearch?
Strengths
Open-source repository released under the Apache-2.0 license
Supports local deployment rather than requiring exclusive use of an online demo
Includes agent, web, inference, and evaluation code
Provides online demos through ModelScope and Hugging Face
Targets long-horizon research tasks and reports results across multiple agentic search benchmarks
Trade-offs
The online demos may have variable response times or fail intermittently because of model latency and tool QPS limits
The repository recommends local deployment for stable use, which adds deployment work
The 30.5 billion total parameter model may be demanding to run locally
›What are DeepResearch’s key features?
Agentic language model designed for long-horizon information-seeking tasks
30.5 billion total parameters with 3.3 billion activated per token
Automated synthetic data pipeline for agentic pre-training, supervised fine-tuning, and reinforcement learning
Agent, web, inference, and evaluation components in the repository
Online demos through ModelScope and Hugging Face
Local deployment option for more stable use
›What are the best use cases for DeepResearch?
Testing an open-source agent on deep information-seeking tasks
Evaluating agentic search performance against benchmarks such as BrowseComp and SimpleQA
Experimenting with synthetic data generation for agent training
Deploying the model locally for research workflows
›What is the pricing for DeepResearch?
Free
›Who is DeepResearch best for?
developersA fit for developers who want to test or deploy an open-source deep-research agent.
researchersUseful for researchers evaluating agentic search, synthetic training data, and long-horizon information seeking.
small teamSmall teams with deployment resources can use the repository for local experimentation and evaluation.
Not for
- Users who need a consistently available hosted service should avoid relying on the online demos because response times may vary or requests may fail.
- Buyers looking for a conventional NLP toolkit rather than a deep-research agent should consider a more narrowly focused tool.
