Quantiphi vs Qubit Labs: full comparison for 2026
Quick verdict
Quantiphi (4.3/5) edges ahead of Qubit Labs (3.7/5) overall. Quantiphi is the better choice for enterprises that need many AI roles filled at once by one AI-only supplier. Qubit Labs is the stronger option for cost-conscious teams that can write a precise brief for an Eastern European ML hire. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs Qubit Labs: head-to-head summary
| Criterion | Quantiphi | Qubit Labs |
|---|---|---|
| Founded | 2013 | 2016 |
| HQ | Marlborough, Massachusetts, USA | Kyiv, Ukraine |
| Team size | 3,000–4,000+ | 50–100 |
| Rating | 4.3 / 5 | 3.7 / 5 |
| Primary differentiator | The biggest AI-only bench here, sold through a named staffing program with AWS | Recruiting across several lower-cost Eastern European countries |
| Pricing model | Elastic Staffing billed per specialist; consulting quoted separately; rates on request | Monthly per engineer with a service fee; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | Healthcare, Financial services, Energy, Retail, Media | Technology, Fintech, E-commerce, Gaming, Healthcare |
Quantiphi vs Qubit Labs: overview
Quantiphi
Quantiphi, based in Marlborough, Massachusetts and founded in 2013, is the largest company on this page that works only on AI and data, with directory estimates between 3,000 and more than 4,000 people. Its Elastic Staffing program, built with AWS, places generative AI and ML specialists into client teams. That scale is the reason it ranks here: no other AI-only supplier can staff ML, MLOps, data and LLM roles in parallel. Google Cloud named it 2025 AI Partner of the Year for North America. The cost is attention, since staffing is one product inside a large consulting business.
Qubit Labs
Qubit Labs launched in 2016 as a Ukrainian IT outstaffing company and is now listed with headquarters in Tallinn or Kyiv depending on the source. It builds remote dedicated teams in Ukraine, Poland, Moldova, Georgia, Romania and other countries, and in recent years it has added AI staff augmentation and deep tech recruiting. Screening is recruiter-led. The firm is a practical option for cost-conscious teams that know exactly what they want, but it has less proven ML depth than AI-only suppliers.
Services and capabilities: Quantiphi vs Qubit Labs
| Capability | Quantiphi | Qubit Labs |
|---|---|---|
| ML engineers | ✓ | ✓ |
| LLM / GenAI engineers | ✓ | ✗ |
| AI agent developers | ✗ | ✗ |
| MLOps engineers | ✓ | ✗ |
| Computer vision engineers | ✓ | ✗ |
| NLP engineers | ✗ | ✗ |
| Data engineers | ✓ | ✓ |
| Engineer-led technical screen | ✗ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
| Direct hire option | ✗ | ✗ |
Tech stack comparison: Quantiphi vs Qubit Labs
| Framework / platform | Quantiphi | Qubit Labs |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | ✓ | N/A |
| Kubernetes | ✓ | N/A |
Pricing comparison: Quantiphi vs Qubit Labs
| Criterion | Quantiphi | Qubit Labs |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Dedicated engineer, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Quantiphi vs Qubit Labs
| Dimension | Quantiphi | Qubit Labs |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Financial services, Energy | Technology, Fintech, E-commerce |
| Best use cases | Staffing eight GenAI specialists into an enterprise program, Adding Vertex AI or SageMaker engineers for a cloud ML migration | Hiring a Python ML engineer in Poland or Romania, Building a remote data team outside Ukraine |
| Typical project type | Dedicated engineer | Dedicated engineer |
Quantiphi vs Qubit Labs: pros and cons
| Quantiphi | |
|---|---|
| + | Can staff several AI specialties in parallel, which no other AI-only firm here can |
| + | Top partner tiers with Google Cloud and AWS help on cloud-specific ML roles |
| + | A named staffing product makes procurement simpler |
| - | Requests for one or two engineers compete with large consulting programs |
| - | Rates appear only after scoping |
| - | Headcount estimates vary widely between sources |
| Qubit Labs | |
|---|---|
| + | Hires in several countries, not only Ukraine |
| + | Lower cost than Western European suppliers |
| + | Clients say shortlists arrive quickly |
| - | Recruiter-led screening for technical roles |
| - | AI staffing is a recent addition |
| - | Headquarters listed differently across sources |
Who should choose Quantiphi?
A typical fit: staffing eight GenAI specialists into an enterprise program.
The biggest AI-only bench here, sold through a named staffing program with AWS. Minimum engagement is not publicly disclosed. Works best with clients in Healthcare, Financial services, Energy, Retail, Media.
Who should choose Qubit Labs?
A typical fit: hiring a Python ML engineer in Poland or Romania.
Recruiting across several lower-cost Eastern European countries. Minimum engagement is not publicly disclosed. Works best with clients in Technology, Fintech, E-commerce, Gaming, Healthcare.
Decision matrix: Quantiphi vs Qubit Labs
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Neither documents an engineer-led screen; run your own technical interview |
| You need one specialist for a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Both; Quantiphi rates higher overall |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| Your budget is at the lower end | Compare: Quantiphi (Not published) vs Qubit Labs (Not published) |
| Your team works U.S. hours | Neither lists Latin American engineers; confirm overlap hours in the contract |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
Use case fit: Quantiphi vs Qubit Labs
| Use case | Quantiphi fit | Qubit Labs fit | Winner |
|---|---|---|---|
| Staffing eight GenAI specialists into an enterprise program | Strong | Limited | Quantiphi |
| Adding Vertex AI or SageMaker engineers for a cloud ML migration | Strong | Strong | Both equally |
| Hiring a Python ML engineer in Poland or Romania | Limited | Strong | Qubit Labs |
| Building a remote data team outside Ukraine | Limited | Strong | Qubit Labs |
Verdict: Quantiphi vs Qubit Labs
Quantiphi (4.3/5) is the stronger overall choice for most AI Engineer Staffing projects. The biggest AI-only bench here, sold through a named staffing program with AWS.
Qubit Labs (3.7/5) is worth a look if you need building a remote data team outside Ukraine. If your situation matches that, Qubit Labs is a competitive option.
Related comparisons
Quantiphi vs Qubit Labs FAQ
Is Quantiphi better than Qubit Labs?
Quantiphi (4.3/5) scores higher overall, but "better" depends on your use case. Quantiphi's strongest advantage: can staff several AI specialties in parallel, which no other AI-only firm here can. Qubit Labs's strongest advantage: hires in several countries, not only Ukraine.
How do Quantiphi and Qubit Labs differ in pricing?
Quantiphi uses elastic staffing billed per specialist; consulting quoted separately; rates on request pricing. Qubit Labs uses monthly per engineer with a service fee; 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: Quantiphi or Qubit Labs?
Quantiphi 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 Quantiphi and Qubit Labs?
Quantiphi's primary differentiator is: the biggest AI-only bench here, sold through a named staffing program with AWS. Qubit Labs's primary differentiator is: recruiting across several lower-cost Eastern European countries. They also differ in team size (3,000–4,000+ vs 50–100), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Financial services vs Technology, Fintech).
Verify all details directly with each company before making a decision.