Agentic AI Comparison:
Consensus vs Kosmos

Consensus: 5

Consensus automates literature search, relevance filtering, and answer generation from scientific papers, but it operates primarily in a query–response paradigm where users pose questions and interpret or act on the results themselves. Features like ResearchGPT and the Co‑Pilot add conversational guidance and workflow support, yet they do not autonomously run multi‑hour research campaigns, execute code, or iteratively refine hypotheses without continuous user steering, which places its autonomy at a moderate level relative to fully agentic research systems.

Kosmos: 10

Kosmos is explicitly designed as an autonomous AI scientist that can run for up to 12 hours, maintaining a structured world model, coordinating multiple agents (literature and data analysis), generating and testing hypotheses, executing ~42,000 lines of code, and producing fully cited scientific reports with minimal human intervention beyond the initial objective and dataset specification. Independent assessments highlight its ability to sustain coherent reasoning over 200+ agent steps and compress months of PhD-level work into a single day, which represents a very high level of autonomy in scientific workflows.

Consensus: 9

Consensus is designed as an intuitive web-based research assistant where users ask natural-language questions and receive summarized answers grounded in cited papers, similar to a specialized search engine. The ResearchGPT and Co‑Pilot experiences further streamline onboarding and workflows by guiding users through questions and follow‑ups, requiring no code, datasets, or complex configuration, which makes the product highly accessible to a wide range of users including non-technical professionals.

Kosmos: 6

Kosmos is accessed through Edison Scientific’s platform and is tailored to technical users who can provide structured research objectives and datasets and interpret complex scientific reports. Its power comes with operational complexity—configuring runs, managing credits, and understanding multi-step analytical outputs—making it more approachable for research labs and data‑savvy teams than for general users, and thus only moderately easy to use overall.

Consensus: 7

Consensus flexibly supports a wide range of question types that can be answered from peer‑reviewed literature, covering topics from medicine to social science, and adapts responses via conversational interfaces such as ResearchGPT. However, it is constrained to literature-grounded insights and does not natively perform custom data analysis, execute code, or coordinate multi‑agent workflows, which limits flexibility for complex experimental or computational research compared to agentic systems.

Kosmos: 8

Kosmos can work across diverse scientific domains such as neuroscience, metabolomics, materials science, and genetics, combining literature review with arbitrary data analysis code and multi-step hypothesis testing. Its architecture—separate agents coordinated by a structured world model—allows flexible research strategies and complex workflows, though its focus remains on data‑driven scientific discovery rather than general-purpose tasks like business writing or casual knowledge queries.

Consensus: 8

Consensus follows a SaaS-style model with free and paid tiers (inferred from its public positioning as a broad-access web app), optimized for high-frequency question answering and research support. Because it does not run long multi‑hour agentic compute campaigns or extensive code execution for each query, its per‑query cost structure is generally lower, making it more economical for everyday research use and for a broader user base.

Kosmos: 6

Kosmos is offered via Edison Scientific with a credit-based pricing model where a full multi‑cycle run consumes a substantial number of credits, reflecting significant compute usage over up to 12 hours of operation. The value per run is high for organizations needing deep research automation, but the per‑run cost and research-oriented positioning make it relatively expensive for casual or frequent small queries compared to typical SaaS research tools.

Consensus: 9

Consensus positions itself as a general-purpose AI research assistant and search platform with a consumer-style web interface, and it is widely referenced as a go‑to tool for evidence-based answers from scientific literature. Its broader target audience, simpler onboarding, and integrations such as ResearchGPT and the Co‑Pilot contribute to higher overall adoption and brand visibility within the academic, professional, and enthusiast research communities.

Kosmos: 6

Kosmos has attracted attention in AI and scientific communities through its arXiv paper and coverage as an advanced autonomous AI scientist, but it is primarily used by research labs and specialized teams rather than the general public. Its niche focus, higher complexity, and credit-based access through Edison Scientific suggest a smaller but highly specialized user base compared to mainstream research assistants.