Mercor AI Research Fund Grants: Benchmarks
关于 MERCOR 的使命是组织人类智能来推动人工智能经济。我们是一家领先的 AI 数据公司，在建立人才专业知识和边界模型之间的层次。平台上的数百万领域专家每天被支付400万美元以上来培训边境 AI 模型.Mercor 的 APEX 基准家族测量了人工智能的实际影响到职业工作上.Mercor 企业将同样的基础设施带给富士顿500强的公司：帮助公司捕捉到他们最好的员工如何真正工作，直接转化这些专业知识为代理商.Mercor 正在创造一个新的类别的工作，其中专业知识驱动人工智能进步。实现这一目标需要一个雄心勃勃，快速和深度承诺的团队。你将与研究人员，运营商和人工智能公司一起工作，在塑造正在重新定义社会的系统方面处于前沿。默科是价值1000亿美元的利性 C 系列公司。我们每周五天在旧金山，纽约或伦敦办事处亲身工作。默克尔 AI 研发基金补贴：本格市场今天面临的最大挑战之一是是否能够在现实世界中提供价值。模型可以在基准上表现得很好，但仍然在生产中难以进行。这就是为什么投资于研究，现实评估和强有力的验证至关重要。默科公司正在寻求资助 AI 比较性分析的研究。这与 MERCOR 研究奖学金分开，该奖学金用于单个专家 （请申请这里 https://www.mercor.com/careers/a0a98be0-d856-4129-b500-c0a3e412ef01/）,我们的5亿美元安全资助奖励 （请申请在这里 https://jobs.ashbyhq.com/mercor/1d59ce50-4207-4d95-b7fd-5a01e90b0897）,以及我们对 AI 经济影响的研究资助。赠款支持：- 来自 MerCor 平台的专家时间 - 研究人员时间 - 费用 - 会议参加费用和 BGETEGORIES 应用程序在三个级别中进行了预算。请在申请中明确说明你的级别，并确保你的整体预算要求符合：- 级别1:不到5万美元：适合专注，精致的项目，如试点研究，评估，复制或扩展现有工作。这些应用程序都经过简单审查。- 级第2:不到200,000美元：适用于需要专门的人员时间，有意义的计算或数据收集的重大项目。与预算分类比较重视进行了更大的审核。
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ABOUT MERCOR
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
MERCOR AI RESEARCH FUND GRANTS: BENCHMARKS
One of the biggest challenges facing the industry today is determining whether frontier AI is capable enough to deliver value in real-world settings. A model can perform well on benchmarks and still struggle in production. That’s why investing in research, realistic evaluations, and robust verification is critical.
Mercor is seeking to fund AI research on benchmarking. This is separate from the Mercor Research Fellowship, which funds individual experts (apply HERE https://www.mercor.com/careers/a0a98be0-d856-4129-b500-c0a3e412ef01/), our $5m of safety funding awards (apply HERE https://jobs.ashbyhq.com/mercor/1d59ce50-4207-4d95-b7fd-5a01e90b0897), and our research funding on the economic impacts of AI.
The grant supports:
- The time of experts from Mercor's platform
- Researcher hours
- API costs
- Stipends for event and conference attendance
BUDGET CATEGORIES
Applications are grouped into three budget tiers. Please state your tier clearly in your application and ensure your overall budget ask falls within it:
- Tier 1: under $50,000: Suited to focused, well-scoped projects such as pilot studies, evaluations, replications, or extensions of existing work. These applications undergo a streamlined review.
- Tier 2: under $200,000: Suited to substantial projects requiring dedicated personnel time, meaningful compute, or data collection. Reviewed with proportionally greater attention to the budget breakdown and implementation plan.
- Tier 3: under $500,000: Reserved for ambitious, multi-component research programs. These applications receive the highest level of scrutiny: reviewers will expect a detailed justification of each spend category, a clear account of team capacity to execute at this scale, and milestones against which progress can be assessed.
The level of review scrutiny scales with the size of the ask, so applicants should request the smallest budget that credibly supports the proposed work.
RESEARCH AGENDA
We are interested in submissions in the following area:
- Real-world evaluations: measuring whether benchmark performance translates into reliable performance on realistic tasks and workflows
- Environments: building high-fidelity, interactive environments that capture the complexity of real-world work
- Long-horizon tasks: evaluating and improving models’ ability to plan, execute, and adapt across extended workflows
- Agentic capabilities: tool use, coordination, memory, and autonomous execution
- Reasoning and problem-solving: improving performance on complex, ambiguous, or underspecified tasks
- Post-training: developing better data, rewards, and training methods to improve model capabilities
- Evaluation methodology: creating more robust measures of capability, reliability, and real-world utility
ELIGIBILITY
- Researchers at universities and non-profit research organizations, as well as public benefit corporations and small startups (<20 people) that do not sell AI training data. Awards are made to the researcher’s institution.
- Applicants must be based in the United States or the United Kingdom
We expect grantees to publish a paper, an open dataset, a public methodology, or a tool the field can use, released under an open license that permits commercial use.
TIMELINE
- Application deadline: November 27, 2026, 11:59 PM PT (UTC−8)
- Notification to applicants: by December 18, 2026
Late or incomplete applications will not be reviewed. All applicants will be notified of the outcome whether or not they are shortlisted.
HOW TO APPLY
We invite interested researchers to submit a brief Expression of Interest (EOI) before preparing a full proposal. The EOI should be ~1–3 pages and include:
- Research question and background (max 250 words): What are you trying to do? State your objective in plain language, with minimal jargon. How is this problem addressed today, and what are the limits of current practice? Who cares: if you succeed, what difference will it make, and to whom?
- Project proposal (max 400 words): Concrete technical and implementation detail: your approach, methods, datasets, models, compute, and evaluation plan.
- Novelty (max 200 words): What is new in your approach relative to existing and ongoing work, and why do you believe it will succeed where current practice falls short?
- Risks (max 150 words): What are the main technical and execution risks, and how will you mitigate or detect them early?
- Team (max 100 words; if the team is large, up to 200): The researchers on the project and their relevant background and prior work.
- Proposed outcomes and timeline: Expected deliverables (papers, artifacts, datasets, tools) and key milestones, including how long the work will take. Include the mid-term and final “exams”: the checkpoints and success criteria by which we will know whether the project is on track and succeeds.
- Budget overview: How much will it cost? Provide a specific overall budget ask, your budget tier (see Budget Categories), and a breakdown by spend category (e.g., personnel, compute, data, travel/other).
- Other sources of funding for this project should be clearly identified in the proposal budget
GUIDANCE FOR APPLICANTS.
- Strong EOIs are specific rather than high-level: they name the methods, systems, and evaluation criteria they will use, and they engage directly with existing literature and ongoing efforts rather than describing the problem space in general terms.
- The EOI should briefly establish the PI’s (and key team members’) relevant background and prior work; proposals without demonstrated expertise in the research area are rarely competitive. Researchers with experience with agentic evaluation, RL environments, and post-training are encouraged to apply
- Proposals that duplicate work already being pursued by many other groups are unlikely to advance unless they offer a clearly differentiated angle.
- Please do not include confidential or proprietary information in your Expression of Interest. Submitting an Expression of Interest does not obligate Mercor to make an award.
AWARD TERMS
Selected grantees will sign Mercor’s research award agreement. Key terms include:
- Grantees keep ownership of their work and grant Mercor a non-exclusive license to use it, including commercially.
- Mercor may identify grantees and their institutions as award recipients, including by name and logo. Grantees may use Mercor’s logo with Mercor’s approval.
- For benchmark and evaluation projects, Mercor receives early access to the benchmark before public release and the exclusive right to build and host a private held-out test set, at Mercor’s cost.
- Grantees agree not to work with specified Mercor competitors on substantially similar benchmarks or evaluations during the award and for 12 months afterward.
- Grantees are free to publish their findings. Mercor reviews drafts in advance only to remove its confidential information.
- Awards are subject to tax documentation, sanctions screening, and periodic progress reports.
ABOUT MERCOR
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents. Mercor is a profitable Series C company valued at $10 billion.