Best ML Model Development Companies

MobiDev vs Grid Dynamics: full comparison for 2026

Last updated: July 2026

Quick verdict

MobiDev (4.3/5) edges ahead of Grid Dynamics (4.0/5) overall. MobiDev is the better choice for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. Grid Dynamics is the stronger option for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. The right choice depends on your project size, budget, and required tech stack.

MobiDev vs Grid Dynamics: head-to-head summary

Criterion MobiDev Grid Dynamics
Founded 2009 2006
HQ Norcross, USA (delivery centers: Lodz, Poland and Chernivtsi, Ukraine) San Ramon, USA
Team size 201–500 1,001–5,000
Rating 4.3 / 5 4.0 / 5
Best for Small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner. Fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.
Pricing model Time & Material, Fixed project Not published; enterprise custom SOWs
Min. engagement Not published Not published
Primary tech stack Python, Computer vision frameworks, Cloud ML platforms Microsoft Azure (AI/ML Advanced Specialization), Python, Kubernetes
Industries served Healthcare, Retail, Manufacturing, Media Retail, Pharmaceuticals, Technology, Financial services

MobiDev vs Grid Dynamics: overview

MobiDev

MobiDev is a software development and consulting company founded in 2009, with business units in Norcross, Georgia (US) and Sheffield (UK), and R&D delivery centers in Lodz, Poland and Chernivtsi, Ukraine staffed by more than 400 engineers. Its consulting services span data science, machine learning, augmented reality, IoT, and DevOps, aimed at small and medium-sized companies rather than large enterprises. The company reports a 100 percent project success rate on Upwork and was named the #1 machine learning development company by Clutch in 2021.

Grid Dynamics

Grid Dynamics Holdings, Inc. was founded in 2006 in Silicon Valley by Victoria Livschitz and went public via a SPAC merger with ChaSerg Technology Acquisition Corp in March 2020, trading on NASDAQ under GDYN. The company reports approximately 5,000 technical professionals delivering MLOps, generative and agentic AI, data platform engineering, recommendation engines, and computer vision work for Fortune 1000 clients, with delivery centers spanning 19 countries. Grid Dynamics holds Microsoft Azure AI/ML Advanced Specialization certification and reported FY2025 revenue of $411.8 million, up 17.5 percent year over year.

Services and capabilities: MobiDev vs Grid Dynamics

Capability MobiDev Grid Dynamics
Custom model training
Fine-tuning & adaptation
MLOps pipeline
Model deployment & serving
Data engineering for ML
ML infrastructure management
Computer vision
NLP & LLM development
Forecasting & time-series modeling
ML strategy consulting

Tech stack comparison: MobiDev vs Grid Dynamics

Framework / platform MobiDev Grid Dynamics
PyTorch N/A N/A
TensorFlow N/A N/A
MLflow N/A N/A
AWS SageMaker N/A N/A
Amazon Bedrock N/A N/A
Google Cloud N/A N/A
Microsoft Azure N/A
Kubernetes
Snowflake N/A N/A
NVIDIA N/A N/A

Pricing comparison: MobiDev vs Grid Dynamics

Criterion MobiDev Grid Dynamics
Minimum engagement Not published Not published
Engagement models Time & Material, Fixed project, Dedicated team Enterprise project engagement, Managed AI services
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: MobiDev vs Grid Dynamics

Dimension MobiDev Grid Dynamics
Best company size Startup to mid-market Startup to mid-market
Best industries Healthcare, Retail, Manufacturing Retail, Pharmaceuticals, Technology
Best use cases Building a custom ML model for a small or medium-sized business without an internal data science team, Combining computer vision or ML work with broader mobile/IoT product development Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor, Building recommendation engines or customer intelligence models at large retail/pharma scale
Typical project type Time & Material Enterprise project engagement

MobiDev vs Grid Dynamics: pros and cons

MobiDev
+ Historical Clutch #1 ranking in machine learning development (2021).
+ 16 Clutch reviews with consistently positive delivery feedback.
+ Explicit focus on small/medium-sized clients, a niche underserved by larger enterprise-first firms.
+ Multi-country delivery footprint (Poland, Ukraine) with 400+ engineers provides meaningful bench depth.
- Team-size figures vary by source (roughly 200–500), indicating some reporting inconsistency.
- SME focus may mean less experience with very large, complex enterprise-scale ML platforms.
- Machine learning is one of several practice areas (alongside AR, IoT) rather than the sole focus.
- Minimum engagement size is not published, requiring a scoping conversation.
Grid Dynamics
+ Publicly traded status (NASDAQ: GDYN) provides audited financial transparency uncommon among private peers.
+ Reported FY2025 revenue of $411.8M with 17.5% year-over-year growth signals strong momentum.
+ Microsoft Azure Advanced Specialization certification in AI/ML.
+ Large delivery footprint (~5,000 technical professionals across 19 countries).
- Enterprise-only focus makes it a poor fit for small or mid-market buyers.
- No clearly located aggregate Clutch/G2 star rating in available public sources.
- Pricing model and minimum engagement are not published (custom SOW-based).
- Named, quantified public case studies (beyond a general pharma recommendation-engine example) are limited in available search results.

Who should choose MobiDev?

MobiDev is the right choice for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..

Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model.. Minimum engagement starts at Not published. Works best with clients in Healthcare, Retail, Manufacturing, Media.

Who should choose Grid Dynamics?

Grid Dynamics is the right choice for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner..

The only publicly traded company (NASDAQ: GDYN) in this comparison among the mid-to-large tier, giving buyers audited financial transparency unavailable from private peers.. Minimum engagement starts at Not published. Works best with clients in Retail, Pharmaceuticals, Technology, Financial services.

Decision matrix: MobiDev vs Grid Dynamics

Your situation Recommended choice
You need full-ownership delivery on a defined project scope MobiDev
You need a large dedicated team for an ongoing programme MobiDev
Your budget is at the lower end Compare: MobiDev (Not published) vs Grid Dynamics (Not published)
You need specialist depth in a specific vertical MobiDev
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build MobiDev

Use case fit: MobiDev vs Grid Dynamics

Use case MobiDev fit Grid Dynamics fit Winner
Building a custom ML model for a small or medium-sized business without an internal data science team Strong Strong Both equally
Combining computer vision or ML work with broader mobile/IoT product development Strong Limited MobiDev
Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor Limited Strong Grid Dynamics
Building recommendation engines or customer intelligence models at large retail/pharma scale Strong Strong Both equally
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Limited Strong Grid Dynamics

Verdict: MobiDev vs Grid Dynamics

MobiDev (4.3/5) is the stronger overall choice for most ML Model Development projects. Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model.. It is best for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner..

Grid Dynamics (4.0/5) is the better choice when fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. If your situation matches those criteria, Grid Dynamics is a competitive option.

Related comparisons

MobiDev vs Grid Dynamics FAQ

Is MobiDev better than Grid Dynamics?

MobiDev (4.3/5) scores higher overall, but "better" depends on your use case. MobiDev is better for small and mid-sized companies wanting a dedicated ML/data-science consulting arm within a broader software development partner.. Grid Dynamics is better for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner..

How do MobiDev and Grid Dynamics differ in pricing?

MobiDev uses time & material, fixed project pricing with a minimum engagement of Not published. Grid Dynamics uses not published; enterprise custom sows pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: MobiDev or Grid Dynamics?

Grid Dynamics 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 MobiDev and Grid Dynamics?

MobiDev's primary differentiator is: historical clutch #1 ranking for machine learning development (2021) combined with a specifically sme-oriented service model.. Grid Dynamics's primary differentiator is: the only publicly traded company (nasdaq: gdyn) in this comparison among the mid-to-large tier, giving buyers audited financial transparency unavailable from private peers.. They also differ in team size (201–500 vs 1,001–5,000), minimum engagement (Not published vs Not published), and primary industries served (Healthcare, Retail vs Retail, Pharmaceuticals).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.