Toptal vs Encora: full comparison for 2026
Quick verdict
Toptal (4.2/5) edges ahead of Encora (4.0/5) overall. Toptal is the better choice for short engagements with one senior AI specialist. Encora is the stronger option for U.S. firms wanting nearshore AI teams from a large provider. The right choice depends on your project size, budget, and required tech stack.
Toptal vs Encora: head-to-head summary
| Criterion | Toptal | Encora |
|---|---|---|
| Founded | 2010 | 2005 |
| HQ | San Francisco, California, USA (remote-first) | Scottsdale, Arizona, USA |
| Team size | 20,000+ network (per company) | 9,500+ |
| Rating | 4.2 / 5 | 4.0 / 5 |
| Primary differentiator | A heavily screened freelance pool that can supply one senior expert quickly | Large Mexican and Latin American delivery base with an AI engineering practice |
| Pricing model | Hourly or weekly freelance billing; $100–$149/hr (Clutch average); no-risk trial period | Dedicated teams; time and materials; 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, Travel |
Toptal vs Encora: 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.
Encora
Encora was founded in 2005 and is headquartered in Scottsdale, Arizona. It took its current name in 2020 after combining subsidiaries including Nearsoft, and it later absorbed Avantica. The company reports more than 9,500 engineers, designers and domain experts across the Americas, Europe, India and Southeast Asia, with AI and LLM engineering among its service lines. In December 2025 the Indian IT firm Coforge agreed to acquire Encora for about $2.35 billion, and Coforge said in April 2026 that all regulatory clearances had been received.
Services and capabilities: Toptal vs Encora
| Capability | Toptal | Encora |
|---|---|---|
| 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 Encora
| Framework / platform | Toptal | Encora |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Toptal vs Encora
| Criterion | Toptal | Encora |
|---|---|---|
| Minimum engagement | $50,000+ typical project size (Clutch) | Not published |
| Engagement models | Part-time fractional experts, Full-time dedicated engineers, Trial period | Dedicated team, Full-time dedicated engineers, Managed delivery |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Toptal vs Encora
| Dimension | Toptal | Encora |
|---|---|---|
| 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 | Building a nearshore team for a SaaS product's AI roadmap, Adding data and LLM engineers to a healthcare platform |
| Typical project type | Part-time fractional experts | Dedicated team |
Toptal vs Encora: 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 |
| Encora | |
|---|---|
| + | Nearshore delivery from Mexico and Latin America on U.S. hours |
| + | Scale to staff several teams at once |
| + | AI work is a named service line with its own platform |
| - | The Coforge acquisition may change account management, pricing and contract terms |
| - | Dedicated teams are the norm, so single-seat placements are less common |
| - | AI depth varies by delivery center |
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 Encora?
A typical fit: building a nearshore team for a SaaS product's AI roadmap.
Large Mexican and Latin American delivery base with an AI engineering practice. Minimum engagement is not publicly disclosed. Works best with clients in Software & SaaS, Healthcare & life sciences, Financial services, Travel.
Decision matrix: Toptal vs Encora
| Your situation | Recommended choice |
|---|---|
| You need a dedicated team for a long programme | Encora |
| You want the supplier to own delivery as well as staffing | Encora |
| 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 Encora (Not published) |
| You need overlap with U.S. working hours | Encora |
| You need specialist depth in a specific vertical | Toptal |
Use case fit: Toptal vs Encora
| Use case | Toptal fit | Encora 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 |
| Building a nearshore team for a SaaS product's AI roadmap | Limited | Strong | Encora |
| Adding data and LLM engineers to a healthcare platform | Limited | Strong | Encora |
Verdict: Toptal vs Encora
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.
Encora (4.0/5) is worth a look if you need adding data and LLM engineers to a healthcare platform. If your situation matches that, Encora is a competitive option.
Related comparisons
Toptal vs Encora FAQ
Is Toptal better than Encora?
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. Encora's strongest advantage: nearshore delivery from Mexico and Latin America on U.S. hours.
How do Toptal and Encora 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). Encora uses dedicated teams; time and materials; 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 Encora?
Toptal 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 Encora?
Toptal's primary differentiator is: a heavily screened freelance pool that can supply one senior expert quickly. Encora's primary differentiator is: large Mexican and Latin American delivery base with an AI engineering practice. They also differ in team size (20,000+ network (per company) vs 9,500+), 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.