Four platforms consistently rise to the top of the AI-training-platform landscape in 2026: Mercor, micro1, Turing, and the Handshake AI Fellowship. They're the ones we feature at the top of the aggregator because they pay the best, screen the most carefully, and route work from frontier labs and serious enterprise customers — not from labeling-platform commodity buyers.
Two of them (Mercor, micro1) we've covered head-to-head in Mercor vs micro1. The other two we cover one-on-one against the field in Mercor vs Handshake AI and micro1 vs Turing. This piece is the four-way buyer's guide — useful if you're deciding which to apply to first, or whether to apply to all four.
TL;DR — the four-way comparison
- Mercor — highest top-end pay ($200+/hr at the ceiling); built for credentialed senior pros (PhDs, FAANG engineers, M.D.s, J.D.s); spiky engagements.
- micro1 — broadest catalog; $40–$150/hr; works for generalists and SMEs alike; lower friction to get in; steadier hours once placed.
- Turing — engineering-heavy; $60–$150/hr for software engineers; coding screen filters out non-engineers; best per-hour for senior engineers willing to clear the bar.
- Handshake AI Fellowship — predictable part-time research-flavored engagements; $75–$125/hr; built around academic credentials (grad students, postdocs, PhDs).
Side-by-side: the pay & access table
Approximate figures for 2026 based on publicly-listed rates and contributor reports. Real placements depend on credentials, niche, and timing.
- Typical pay range · Mercor $80–$200/hr · micro1 $40–$90/hr · Turing $60–$120/hr (eng) / $40–$80/hr (non-eng) · Handshake $75–$125/hr
- High-end peak · Mercor $200+/hr · micro1 $150/hr · Turing $150/hr · Handshake $125/hr
- Application format · Mercor AI interview (45–90 min) · micro1 AI interview (15–30 min) · Turing AI interview + coding screen · Handshake résumé + research statement + human or AI screen
- Time from apply → first engagement · Mercor 2–6 weeks · micro1 1–2 weeks · Turing 1–3 weeks · Handshake 2–4 weeks
- Hours pattern · Mercor spiky (intense bursts + gaps) · micro1 steady (broad catalog, easy to refill) · Turing client-clustered (long engagements with one client) · Handshake predictable part-time (10–20 hrs/week, fixed term)
- Best fit · Mercor senior credentialed pros · micro1 generalists and broad SMEs · Turing software engineers · Handshake grad students, postdocs, researchers
Each platform's strongest pitch
Mercor — for senior credentialed pros
Mercor pays the most at the top, full stop. If you have a verifiable senior credential — 5+ years at a FAANG-equivalent, an M&A practice, a top-tier consulting shop, an audit partnership, or a practicing M.D./J.D. background — Mercor is the highest- return application you can send in this space. The price is a harder interview (45–90 minutes of AI-led depth probing) and a spiky engagement pattern: you don't pick roles, and there's a wait between placements. See the full review for application tactics — Mercor review.
micro1 — for breadth and steadier hours
micro1 is the platform we'd apply to first for almost anyone without a domain that explicitly fits the other three. The catalog is the widest, the interview is the fastest, and once you're in, the broad role catalog means you can refill hours when one engagement ends. Pay is competitive but flatter than Mercor's; the top end caps around $150/hr. See the full review — micro1 review.
Turing — for software engineers
Turing's AI-training arm pays software engineers more than micro1 and tends to surface more roles that genuinely match an engineer's skill set (code generation evaluation, code review on real codebases, stack-specific expert work). The coding screen is a real filter — non-engineers shouldn't bother — but engineers who clear it routinely earn $90–$150/hr on engagement-specific work.
Handshake AI — for academic credentials and predictable hours
The Handshake AI Fellowship is structurally different from the other three. It's a part-time fellowship model with defined hours, a defined scope, and a defined timeline. Pay is $75–$125/hr — high enough to be worth your time, low enough that senior credentialed pros will earn more on Mercor. The right fit is graduate students, postdocs, recent PhDs, or academic researchers who want structured weekly hours rather than spot-market gigs. See the head-to-head with Mercor — Mercor vs Handshake AI.
Decision matrix — which to apply to first
Plain English. If multiple branches fit, apply to all of them in parallel.
- I'm a senior engineer at FAANG or equivalent → Mercor + Turing. Apply both same evening. Mercor for the spiky high-pay placements, Turing for the steady-engineer catalog.
- I'm an engineer (any seniority) but not senior-FAANG → Turing + micro1. Turing for the higher engineering rates, micro1 for breadth in case Turing's coding screen knocks you out.
- I'm a PhD candidate or postdoc → Handshake + Mercor. Handshake for the structured fellowship engagements, Mercor if you have applied research to leverage for SME work.
- I'm an M.D., J.D., or audit-partner-level professional → Mercor first, then Handshake as a fallback. Mercor's top-end SME rates for these credentials are the highest in the market.
- I'm a strong professional generalist without an advanced degree → micro1 only. The other three expect credentials they can probe.
- I'm a master's student or early-career researcher → Handshake first, then micro1 in parallel. Mercor and Turing both expect more seniority.
- I'm a college student or absolute beginner → none of these yet. Start with the lower-bar platforms in our no-experience guide to build a track record first.
Running all four — is it worth it?
For some people, yes. The top earners in this space typically run two or three of these platforms simultaneously and let them compete for their time. None has a platform-level exclusivity clause; per-engagement NDAs and non-competes exist but they're per-engagement, not per-platform.
The honest practical reality: if you're a senior engineer with a PhD and 8 years of FAANG experience, all four would accept you and you'd cherry-pick the best-paying engagement at any given moment. If you're a strong-but-not-elite contributor, two platforms is usually plenty — more than that just adds operational overhead (separate 1099s, separate invoices, separate scheduling) without much marginal upside.
Operationally: track hours separately, expect a 1099-NEC from each at year-end, and read per-engagement NDA language — those bind you to a specific client, not the platform. For the tax mechanics of running 1099 work across multiple platforms, see our AI training taxes guide.
How we picked these four
We feature these four because, across roughly two years of watching the AI-training-platform landscape, they consistently do four things commodity platforms don't: (1) publish pay ranges openly, (2) pay weekly or biweekly without minimum-payout nonsense, (3) route to frontier labs or serious enterprise customers rather than spam-quality buyers, and (4) treat contributors as contractors with real engagement, not as anonymous labelers behind a queue. There are other good platforms in the broader catalog; these four are the ones we'd apply to first.
For the wider field, including platforms outside our featured zone, see the best AI training platforms guide. For pay-tier context across the whole market, see the AI training pay breakdown.