Toptal vs Nearsure: full comparison for 2026
Quick verdict
Toptal (4.2/5) edges ahead of Nearsure (3.9/5) overall. Toptal is the better choice for short engagements with one senior AI specialist. Nearsure is the stronger option for U.S. teams adding Latin American GenAI developers. The right choice depends on your project size, budget, and required tech stack.
Toptal vs Nearsure: head-to-head summary
| Criterion | Toptal | Nearsure |
|---|---|---|
| Founded | 2010 | 2018 |
| HQ | San Francisco, California, USA (remote-first) | Montevideo, Uruguay (U.S.-incorporated) |
| Team size | 20,000+ network (per company) | 500–850 (sources vary) |
| Rating | 4.2 / 5 | 3.9 / 5 |
| Primary differentiator | A heavily screened freelance pool that can supply one senior expert quickly | Augmentation-first business model with a growing AI studio |
| Pricing model | Hourly or weekly freelance billing; $100–$149/hr (Clutch average); no-risk trial period | Monthly staff augmentation rates; project development; rates on request |
| Min. engagement | $50,000+ typical project size (Clutch) | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, OpenAI, AWS |
| Industries served | Software & SaaS, Financial services, Media, Healthcare & life sciences | Software & SaaS, Healthcare & life sciences, Financial services |
Toptal vs Nearsure: overview
Toptal
Toptal was founded in 2010 and lists a San Francisco address, though it operates as a fully remote company. It is a freelance marketplace that says it accepts only the top 3% of applicants into a network of more than 20,000 professionals across engineering, design and finance. Clutch lists an average rate of $100 to $149 per hour and a typical project minimum of $50,000. Toptal matches individual contractors and does not employ the engineers it places.
Nearsure
Nearsure started operations in 2018 under co-founder and CEO Giuliana Corbo and is described by Bloomberg as a Uruguayan IT services company, though it is incorporated in the United States. Bloomberg reported a 2024 plan to grow to about 850 staff. Remote staff augmentation for U.S. clients is its core business, and the service list has widened to generative AI, cloud migration and Salesforce work through a Data & AI studio.
Services and capabilities: Toptal vs Nearsure
| Capability | Toptal | Nearsure |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| MLOps & deployment | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| Data engineering | ✗ | ✓ |
| AI agent development | ✗ | ✗ |
| Fractional / part-time experts | ✓ | ✗ |
| Risk-free trial period | ✓ | ✗ |
| Nearshore time-zone overlap | ✗ | ✓ |
Tech stack comparison: Toptal vs Nearsure
| Framework / platform | Toptal | Nearsure |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Databricks | N/A | N/A |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Toptal vs Nearsure
| Criterion | Toptal | Nearsure |
|---|---|---|
| Minimum engagement | $50,000+ typical project size (Clutch) | Not published |
| Engagement models | Part-time fractional experts, Full-time dedicated engineers, Trial period | Full-time dedicated engineers, Dedicated team |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Toptal vs Nearsure
| Dimension | Toptal | Nearsure |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Software & SaaS, Financial services, Media | Software & SaaS, Healthcare & life sciences, Financial services |
| Best use cases | Hiring an ML architect for a six-week design review, Getting a second opinion on an LLM evaluation approach | Adding a GenAI developer to a U.S. SaaS team, Staffing data engineers for a cloud migration |
| Typical project type | Part-time fractional experts | Full-time dedicated engineers |
Toptal vs Nearsure: pros and cons
| Toptal | |
|---|---|
| + | Strict acceptance screening filters out most weak candidates |
| + | Part-time and hourly arrangements suit advisory or review work |
| + | A trial period lowers the cost of a bad match |
| - | Clutch's $100–$149 hourly average is high for long-term team building |
| - | Freelancers can leave between engagements, taking system knowledge with them |
| - | General screening is not specific to ML depth |
| Nearsure | |
|---|---|
| + | Staff augmentation is the main business, so processes are built around it |
| + | Latin American engineers on U.S. hours |
| + | Has been profitable since early in its history, per AméricaEconomía |
| - | AI is a newer studio inside a general staffing company |
| - | Headcount reports vary between 525 and 850 |
| - | HQ location differs between sources |
Who should choose Toptal?
A typical fit: hiring an ML architect for a six-week design review.
A heavily screened freelance pool that can supply one senior expert quickly. Minimum engagement starts at $50,000+ typical project size (Clutch). Works best with clients in Software & SaaS, Financial services, Media, Healthcare & life sciences.
Who should choose Nearsure?
A typical fit: adding a GenAI developer to a U.S. SaaS team.
Augmentation-first business model with a growing AI studio. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Healthcare & life sciences, Financial services.
Decision matrix: Toptal vs Nearsure
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Nearsure |
| You want the supplier to own delivery as well as staffing | Neither offers managed delivery; you will lead the work |
| You need one expert part-time | Toptal |
| You want to test an engineer before signing for months | Toptal |
| Your budget is at the lower end | Compare: Toptal ($50,000+ typical project size (Clutch)) vs Nearsure (Not published) |
| You need overlap with U.S. working hours | Nearsure |
| You need specialist depth in a specific vertical | Toptal |
Use case fit: Toptal vs Nearsure
| Use case | Toptal fit | Nearsure fit | Winner |
|---|---|---|---|
| Hiring an ML architect for a six-week design review | Strong | Limited | Toptal |
| Getting a second opinion on an LLM evaluation approach | Strong | Limited | Toptal |
| Adding a GenAI developer to a U.S. SaaS team | Limited | Strong | Nearsure |
| Staffing data engineers for a cloud migration | Limited | Strong | Nearsure |
Verdict: Toptal vs Nearsure
Toptal (4.2/5) is the stronger overall choice for most AI Staff Augmentation projects. A heavily screened freelance pool that can supply one senior expert quickly.
Nearsure (3.9/5) is worth a look if you need staffing data engineers for a cloud migration. If your situation matches that, Nearsure is a competitive option.
Related comparisons
Toptal vs Nearsure FAQ
Is Toptal better than Nearsure?
Toptal (4.2/5) scores higher overall, but "better" depends on your use case. Toptal's strongest advantage: strict acceptance screening filters out most weak candidates. Nearsure's strongest advantage: staff augmentation is the main business, so processes are built around it.
How do Toptal and Nearsure differ in pricing?
Toptal uses hourly or weekly freelance billing; $100–$149/hr (clutch average); no-risk trial period pricing with a minimum engagement of $50,000+ typical project size (Clutch). Nearsure uses monthly staff augmentation rates; project development; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Toptal or Nearsure?
Nearsure is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between Toptal and Nearsure?
Toptal's primary differentiator is: a heavily screened freelance pool that can supply one senior expert quickly. Nearsure's primary differentiator is: augmentation-first business model with a growing AI studio. They also differ in team size (20,000+ network (per company) vs 500–850 (sources vary)), minimum engagement ($50,000+ typical project size (Clutch) vs Not published), and primary industries served (Software & SaaS, Financial services vs Software & SaaS, Healthcare & life sciences).
Verify all details directly with each company before making a decision.