How many reqs per recruiter? 2026 benchmarks and how to set your own

As of October 2026, the most solid published benchmark comes from Gem: its 2026 Recruiting Benchmarks Report says recruiters manage 13.4 open roles at a time, and its 2025 report put the 2024 average at 14 job reqs per recruiter, up from 9 in 2021. Those are averages of what recruiters at Gem's customers actually carry, not a recommended load. The right number for your team depends on how hard the roles are, how much sourcing and coordination support recruiters have, and how quickly hiring managers respond, and you can calculate it from hours or from your own throughput.

This page gives the benchmark with its definitions, explains who it does and does not describe, and sets out three ways to work out your own number. To turn that into a hiring plan for next year, use the recruiting capacity planning template.

What do the published benchmarks say?

Gem's 2025 Recruiting Benchmarks Report defines job openings per recruiter as "the average number of job reqs a given recruiter is working on simultaneously on any given day in a given year". Its data covers January 2021 to December 2024: over 140 million applicants, 14.4 million candidates and 1.3 million hires. By company size:

Gem notes that the aggregate is higher than most size bands because it includes companies of unknown size that the size breakdown leaves out. By industry, its 2024 figures were 10 for computer software, 9 for IT services and hardware, 11 for life sciences, 12 for manufacturing and 14 for financial services.

The newer headline is in Gem's key takeaways from the 2026 Recruiting Benchmarks Report (posted December 1, 2025): "Recruiters are managing 13.4 open roles at a time", from data on over 165 million applications, 15 million candidates and 1.2 million hires. The same post says the average number of interviews per hire has risen 33% since 2021, which matters for capacity: the same req now takes more coordination than it did.

Other figures for reqs per recruiter circulate widely, usually without a sample, a definition or a named publisher. We have only used numbers whose publisher, definition and data we could read.

Who do these numbers describe, and who do they not?

• Employers using Gem. The data comes from companies using Gem's recruiting software, segmented by their own headcount, industry and department, so it describes employers recruiting for themselves. It is a reasonable reference for corporate talent acquisition.
• Not agency desks. A contingent recruiter's job orders are not the same unit: many are competed with other agencies, some are never seriously worked, and the measure that matters is fills per job order. See recruiting agency metrics for agency definitions.
• Not volume hiring without adjustment. A req is a req in this measure. One requisition for 30 warehouse associates and one for a single VP of Finance both count as one, though the work could not be more different.
• An average, not a ceiling. Gem's report frames the rise as growing strain on recruiters, not as a target. Matching the average tells you that you are typical, not that your recruiters are well loaded.

Why does one number not fit every team?

How do you calculate the right load for your team?

Method 1: hours (the one to start with)

1. Available hours. Weekly hours × the share left for req work after team meetings, admin and training. Measure it; do not guess.
2. Hours per req per week, by tier. Have recruiters log time against each req for two normal weeks, then average by difficulty tier.
3. Capacity. Available hours ÷ hours per req, for the mix of tiers the recruiter actually holds.

Worked example with invented numbers: a recruiter works 40 hours and spends 75% on req work, so 30 hours. Logged time shows a hard req takes 6 hours a week, a standard req 3, and a repeatable req 1.5. Two hard reqs (12 hours), four standard (12) and four repeatable (6) fill the 30 hours: ten reqs is full capacity for that mix. Swap two repeatable reqs for two hard ones and capacity falls to eight. This is why a flat number, from Gem or anyone else, cannot be the target on its own.

Method 2: throughput (the sanity check)

Over time, the average number of reqs a recruiter carries is roughly the number they close each month multiplied by the average number of months a req stays open. Example: a recruiter closes three reqs a month, and reqs stay open 2.5 months on average, so a steady load is about 7.5. If that recruiter actually carries 14, either reqs are staying open far longer than 2.5 months or many of them are not being worked. Either way, the extra reqs are not extra output; they are waiting. Pull the oldest ones and ask whether each should be prioritized, paused or closed (see how to prioritize open requisitions).

Method 3: historical productivity (for planning a year ahead)

Gem's 7-step guide to capacity planning works from hires rather than reqs: divide past hires in a department by the recruiters who made them to get productivity per recruiter, using two years of data to smooth out seasons and removing anomalies such as a hiring freeze. It suggests weighting roles by difficulty, noting that tech roles are generally twice as hard to fill, and that a ramping recruiter may only be expected to hire at 50% capacity. Multiply productivity by recruiters to forecast what the team can deliver, then compare it with the hiring plan.

How should you weight reqs by difficulty?

Weights let you compare loads fairly. Agree three or four tiers and a weight for each, based on the hours logged in method 1. As an example only: repeatable 0.5, standard 1, hard 2, executive or first-of-kind 3. A recruiter with four standard and two hard reqs carries a weighted load of 8; one with ten repeatable reqs carries 5, despite having more reqs. Our guide to recruiter productivity metrics uses the same weights to compare output, so load and output are measured on one scale.

What are the signs a recruiter is over capacity?

• Reqs with no activity for seven days or more.
• Time to first submittal rising on new reqs.
• Candidates waiting more than two working days for a reply after an interview.
• Screen notes getting shorter, later or missing, so hiring managers ask for information that should be in the record.
• Hiring managers escalating to the recruiter's manager.
• Interviews booked without a prep call or a kit.

Any two of these together are a stronger signal than any req count. They are also visible on a desk-level dashboard; see the recruiter KPI dashboard template.

What do you do when the load is too high?

1. Prioritize and pause. Rank reqs by impact, difficulty, manager engagement and urgency, and pause the bottom of the list openly with the hiring leader rather than working everything a little.
2. Add support before headcount. A sourcer or coordinator often adds more capacity than another generalist recruiter, because sourcing and scheduling are the hours that grow fastest with load.
3. Cut admin per call. Notes, scorecards and submittals after every screen are a large, measurable block of hours; see how to cut recruiter admin time with AI for how to measure it before buying anything.
4. Rebalance by weight. Move reqs between recruiters using weighted load, not raw counts.
5. Make the case for headcount with the model. Hours available, hours needed and the gap, by quarter, is a far stronger argument than "everyone is busy".