Best ML Model Development Companies

Grid Dynamics vs Globant: full comparison for 2026

Last updated: July 2026

Quick verdict

Grid Dynamics (4.0/5) edges ahead of Globant (3.9/5) overall. Grid Dynamics is the better choice for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. Globant is the stronger option for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting.. The right choice depends on your project size, budget, and required tech stack.

Grid Dynamics vs Globant: head-to-head summary

Criterion Grid Dynamics Globant
Founded 2006 2003
HQ San Ramon, USA Luxembourg City, Luxembourg
Team size 1,001–5,000 10,000+
Rating 4.0 / 5 3.9 / 5
Best for Fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner. Large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting.
Pricing model Not published; enterprise custom SOWs Not published; moving toward subscription-style pricing for AI Pods (per third-party commentary; independently unverifiable in detail)
Min. engagement Not published Not published
Primary tech stack Microsoft Azure (AI/ML Advanced Specialization), Python, Kubernetes Proprietary Glob.AI OS platform, Computer vision (via Synthesis AI partnership), Cloud ML platforms
Industries served Retail, Pharmaceuticals, Technology, Financial services Financial services, Life sciences, Airlines/travel, Sports and entertainment

Grid Dynamics vs Globant: overview

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.

Globant

Globant was founded in 2003 in Buenos Aires by Martin Migoya, Guibert Englebienne, Martin Umaran, and Nestor Nocetti, and is now headquartered in Luxembourg while trading publicly on the NYSE under GLOB. The company reports roughly 29,000 employees and organizes its AI capability around eight industry-specific studios that produce what it calls "AI Pods," tailored solutions for specific industry challenges spanning financial services, life sciences, and airlines among others. Globant was recognized by IDC MarketScape as a Worldwide Leader in AI Services in 2023, and has named client work including LALIGA for agentic AI in sports, presented at NVIDIA GTC 2026.

Services and capabilities: Grid Dynamics vs Globant

Capability Grid Dynamics Globant
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: Grid Dynamics vs Globant

Framework / platform Grid Dynamics Globant
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 N/A
Snowflake N/A N/A
NVIDIA N/A N/A

Pricing comparison: Grid Dynamics vs Globant

Criterion Grid Dynamics Globant
Minimum engagement Not published Not published
Engagement models Enterprise project engagement, Managed AI services Studio-based engagement, Enterprise project engagement, Subscription (AI Pods)
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Grid Dynamics vs Globant

Dimension Grid Dynamics Globant
Best company size Startup to mid-market Enterprise
Best industries Retail, Pharmaceuticals, Technology Financial services, Life sciences, Airlines/travel
Best use cases Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor, Building recommendation engines or customer intelligence models at large retail/pharma scale Large enterprises wanting pre-packaged, industry-specific AI solutions delivered quickly via studio teams, Sports, entertainment, or media companies exploring agentic AI applications
Typical project type Enterprise project engagement Studio-based engagement

Grid Dynamics vs Globant: pros and cons

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.
Globant
+ IDC MarketScape Worldwide Leader in AI Services (2023), an independently sourced third-party analyst validation.
+ Named, checkable client work (LALIGA agentic AI, presented publicly at NVIDIA GTC 2026).
+ Industry-specific studio model can accelerate time-to-value versus fully custom engagements.
+ Publicly traded (NYSE: GLOB) with substantial scale (29,000+ employees).
- Studio/Pod delivery model provides less MLOps/infrastructure-specific documented depth than peers like EPAM or Persistent.
- No clearly located aggregate Clutch/G2 star rating in available public sources.
- Pricing details, including the reported move to subscription models, are not fully independently verifiable.
- Large scale means individual client attention may vary depending on which studio is engaged.

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.

Who should choose Globant?

Globant is the right choice for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting..

Only company in this list organized around a formal "studio + AI Pods" delivery model, and the only one with an IDC MarketScape Worldwide Leader in AI Services designation.. Minimum engagement starts at Not published. Works best with clients in Financial services, Life sciences, Airlines/travel, Sports and entertainment.

Decision matrix: Grid Dynamics vs Globant

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

Use case fit: Grid Dynamics vs Globant

Use case Grid Dynamics fit Globant fit Winner
Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor Strong Limited Grid Dynamics
Building recommendation engines or customer intelligence models at large retail/pharma scale Strong Limited Grid Dynamics
Large enterprises wanting pre-packaged, industry-specific AI solutions delivered quickly via studio teams Strong Strong Both equally
Sports, entertainment, or media companies exploring agentic AI applications Limited Strong Globant
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Strong Limited Grid Dynamics

Verdict: Grid Dynamics vs Globant

Grid Dynamics (4.0/5) is the stronger overall choice for most ML Model Development projects. 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.. It is best for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner..

Globant (3.9/5) is the better choice when large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting.. If your situation matches those criteria, Globant is a competitive option.

Related comparisons

Grid Dynamics vs Globant FAQ

Is Grid Dynamics better than Globant?

Grid Dynamics (4.0/5) scores higher overall, but "better" depends on your use case. Grid Dynamics is better for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. Globant is better for large enterprises wanting industry-specific pre-packaged AI solutions ("AI Pods") delivered through a studio-based model rather than fully bespoke consulting..

How do Grid Dynamics and Globant differ in pricing?

Grid Dynamics uses not published; enterprise custom sows pricing with a minimum engagement of Not published. Globant uses not published; moving toward subscription-style pricing for ai pods (per third-party commentary; independently unverifiable in detail) 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: Grid Dynamics or Globant?

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 Grid Dynamics and Globant?

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.. Globant's primary differentiator is: only company in this list organized around a formal "studio + ai pods" delivery model, and the only one with an idc marketscape worldwide leader in ai services designation.. They also differ in team size (1,001–5,000 vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Retail, Pharmaceuticals vs Financial services, Life sciences).

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