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Groq vs Modal Comparison

Last updated:

Groq

4.6(310 reviews)

Starting at Free free

  • Small Business
  • Mid-Market

Groq is an AI inference company that provides the fastest publicly available LLM API, powered by its proprietary Language Processing Units (LPUs). Where GPU-based inference delivers 50-100 tokens/second, Groq routinely h…

Modal

4.7(185 reviews)

Starting at Free free

  • Small Business
  • Mid-Market

Modal is a serverless cloud platform for running Python code on GPUs and CPUs in the cloud with zero infrastructure management. Developers define functions with a Python decorator, and Modal handles containerization, GPU…

Modal leads on user satisfaction with a 4.7-star rating across 185 reviews.

Groq vs Modal — at a glance

FeatureGroqModal
Rating4.6 / 54.7 / 5
Reviews310185
Starting priceFree freeFree free
Free trial No No
Free version No No
Best forSmall Business, Mid-Market, EnterpriseSmall Business, Mid-Market, Enterprise
CategoryGenerative AI Infrastructure SoftwareCloud Platform as a Service (PaaS) Software
PlatformsCloud, On-PremiseCloud
APIAvailableAvailable
Support modesDeveloper Discord, Help Center, Email Support, Enterprise SupportCommunity Slack, Help Center, Email Support, Enterprise Support

Key differences between Groq and Modal

  • Pricing: Groq starts at Free free, while Modal starts at Free free.
  • User satisfaction: Modal scores higher with a 4.7-star average.
  • Deployment: Groq supports Cloud, On-Premise; Modal supports Cloud.

Groq vs Modal — find the better fit before you commit.

01

Which tool fits your team best

02

Which is actually cheaper for your team size

03

Where each product wins, per real buyers

Most Generative AI Infrastructure Software tools look identical on paper. This comparison cuts to the differences that matter — pricing structure, team fit, and what real buyers found after signing up.

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Groq vs Modal: Biggest differences

Start here before you go deeper into features.

Groq

Best for

Small Business, Mid-Market, Enterprise

Modal

Best for

Small Business, Mid-Market, Enterprise

Groq typically suits Small Business and Mid-Market. Modal tends to fit Small Business and Mid-Market better. The right choice depends on your team size, workflow, and whether a free trial matters.

Description

Groq is an AI inference company that provides the fastest publicly available LLM API, powered by its proprietary Language Processing Units (LPUs). Where GPU-based inference delivers 50-100 ... Read More about Groq

Modal is a serverless cloud platform for running Python code on GPUs and CPUs in the cloud with zero infrastructure management. Developers define functions with a Python decorator, and ... Read More about Modal

Entry Level Pricing

  • Starts from Free
  • Starts from Free

Free Trial Availability

  • No free trial
  • No free trial

SpotScore

What's this? ↗

9.2/10

9.4/10

User Ratings

Based on verified Spotsaas reviews
Get pricing help
Get pricing help

Where each option fits best

See where each product is strongest, which teams it fits, and what causes buyers to keep looking — before you commit.

Based on buyer reviews and verified product data collected by Spotsaas.

Strengths

Key strengths

Groq

  • Real-Time AI Interactions: At 500+ tokens/second, Groq lets you get AI responses that feel instantaneous — important for voice agents, live coding assistants, and customer-facing chatbots.
  • Drop-In OpenAI Replacement: OpenAI SDK compatibility means switching from GPT-3.5 to Groq-hosted Llama 3 requires changing one line of code — no integration work.
  • Cost Efficiency at Scale: Groq's per-token pricing for open-source models is significantly cheaper than proprietary model APIs at comparable intelligence levels.

Modal

  • GPU in One Line of Python: `@app.function(gpu="A100")` is the entire infrastructure declaration — no Dockerfile, no Kubernetes manifest, no capacity planning.
  • Cost-Efficient Experimentation: Per-second billing with no minimums means ML experiments and fine-tuning runs cost only their actual compute time, eliminating reserved instance waste.
  • Scalable Batch Processing: Modal scales to thousands of parallel function invocations automatically, enabling large-scale data processing and batch inference jobs without cluster management.
Best fit

Best fit

Groq

  • Voice AI companies needing sub-200ms LLM response times for natural-feeling conversational agents
  • Coding assistant products requiring real-time code generation without the lag of GPU inference
  • Teams replacing GPT-3.5 with open-source Llama 3 on Groq for cost reduction at high API call volumes

Modal

  • ML researchers running fine-tuning and evaluation jobs on H100s without managing cloud infrastructure
  • Generative AI startups serving model inference at variable traffic levels with per-second cost efficiency
  • Data engineering teams running large-scale Python batch jobs on GPU clusters without DevOps overhead

Software Demo

Demo

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How do Groq and Modal Compare on Features?

Total Features

4 Features

6 Features

Unique Features

No unique features

No unique features

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Compare Groq and Modal on pricing

Review starting price, plan structure, and free-trial access side by side so you can see which option fits your budget and buying process.

Pricing Option

      Starting From

      • Free
      • Free

      Pricing Plans

      • Free

        Free

        • Rate-limited API access

        • All public models

        • Developer console

        Show more +

      • Developer

        Custom

        paid

        • Higher rate limits

        • Pay-per-token

        • All models

        Show more +

      • Enterprise

        Custom

        paid

        • Dedicated capacity

        • SLA

        • On-premise LPU option

        Show more +

      • Free

        Free

        • $30 credits/month

        • All GPU types

        • Full feature access

        Show more +

      • Pay-as-you-go

        Custom

        paid

        • All GPUs

        • No idle charges

        • Standard support

        Show more +

      • Enterprise

        Custom

        paid

        • Volume discounts

        • Dedicated capacity

        • SLA

        Show more +

      Groq vs Modal: Other Details

      Organization Types supported

      • Large Enterprises
      • Medium Business
      • Small Business
      • Individuals
      • Freelancers
      • Large Enterprises
      • Medium Business
      • Small Business
      • Individuals
      • Freelancers

      Platforms Supported

      • Browser Based (Cloud)
      • Browser Based (Cloud)
      • Mobile - Android
      • Browser Based (Cloud)
      • Browser Based (Cloud)
      • Mobile - Android

      Modes of support

      • 24/7 (Live rep)
      • Business Hours
      • Online
      • 24/7 (Live rep)
      • Business Hours
      • Online

      API Support

      • Available
      • Available
      Get help choosing
      Get help choosing

      Groq User Reviews & Rating Comparison

      User Ratings

      4.6

      (based on 310 reviews)

      4.7

      (based on 185 reviews)

      Rating Distribution

      0

      0

      0

      0

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      0

      0

      0

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      Spotsaas Editor’s POV generated by AI

      Buyer sentiment

      Buyer sentiment is very strong across 310 reviews, with consistently positive feedback.

      What buyers like

      • 5-10x faster than GPU-based inference — the speed difference is perceptible in real-time applications like voice agents and interactive coding assistants.
      • OpenAI-compatible API means existing applications built on the OpenAI SDK can switch to Groq with a single environment variable change.
      • Free tier with generous rate limits makes evaluation and prototyping accessible without upfront cost commitment.

      Common complaints

      • Model selection is limited to open-source models (Llama, Mixtral, Gemma) — teams requiring GPT-4 or Claude must use other providers.
      • Free tier rate limits are hit quickly at production volumes; scaling to meaningful throughput requires transitioning to paid usage-based pricing.

      Buyer sentiment

      Buyer sentiment is very strong across 185 reviews, with consistently positive feedback.

      What buyers like

      • Zero infrastructure management — no Kubernetes, Docker registries, or EC2 instance sizing; a Python decorator is the entire deployment interface.
      • Per-second billing with no idle charges makes GPU-intensive experiments cost-efficient; teams only pay for actual compute time, not reserved instances that sit idle.
      • H100 and A100 GPU access on-demand with auto-scaling means small teams can run large-scale training or inference jobs that would otherwise require negotiating reserved GPU capacity.

      Common complaints

      • Cold start latency when containers spin up from idle can add 1-5 seconds to first requests — problematic for low-latency user-facing inference endpoints.
      • Vendor-specific Python API means Modal code is not portable to other cloud providers without refactoring.

      Pros and Cons

      • 5-10x faster than GPU-based inference — the speed difference is perceptible in real-time applications like voice agents and interactive coding assistants.

      • OpenAI-compatible API means existing applications built on the OpenAI SDK can switch to Groq with a single environment variable change.

      • Free tier with generous rate limits makes evaluation and prototyping accessible without upfront cost commitment.

      • Model selection is limited to open-source models (Llama, Mixtral, Gemma) — teams requiring GPT-4 or Claude must use other providers.

      • Free tier rate limits are hit quickly at production volumes; scaling to meaningful throughput requires transitioning to paid usage-based pricing.

      • Zero infrastructure management — no Kubernetes, Docker registries, or EC2 instance sizing; a Python decorator is the entire deployment interface.

      • Per-second billing with no idle charges makes GPU-intensive experiments cost-efficient; teams only pay for actual compute time, not reserved instances that sit idle.

      • H100 and A100 GPU access on-demand with auto-scaling means small teams can run large-scale training or inference jobs that would otherwise require negotiating reserved GPU capacity.

      • Cold start latency when containers spin up from idle can add 1-5 seconds to first requests — problematic for low-latency user-facing inference endpoints.

      • Vendor-specific Python API means Modal code is not portable to other cloud providers without refactoring.

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      Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].

      Frequently asked questions

      Which is better, Groq or Modal?
      Modal edges out the other on user ratings (4.7 vs 4.6). That said, the best pick depends on your use case — use the comparison tables above to evaluate each dimension.
      Do Groq and Modal offer a free trial?
      Neither Groq nor Modal currently lists a free trial.
      What is the starting price of Groq vs Modal?
      Groq starts at Free free. Modal starts at Free free.