StackMatch / Compare / Modal vs Groq
Honest Tool Comparison

Modal vs Groq

An honest, context-aware comparison. No affiliate links. No paid placements. Just the data that helps you decide.

Modal

free
Cloud Infrastructure & DevOps

Serverless compute for AI — run Python functions on GPUs with one decorator, no infra to manage.

Free: $30/month compute credit. Pay-as-you-go: GPU from $0.59/hour (T4) to $6.25/hour (H100). Enterprise: custom.

Groq

starter
Cloud Infrastructure & DevOps

Ultra-low-latency LLM inference on custom LPU chips — the fastest way to serve open-weights models.

Free tier available. GroqCloud pay-per-token pricing: LLaMA 3.3 70B ~$0.59/1M input, $0.79/1M output. Enterprise: custom.

StackMatch Editorial verdicts

Bylined · No vendor influence
ModalBUY
Serverless Python compute that feels like local

Modal is the best developer experience for running Python workloads (ML, data pipelines, batch jobs) in the cloud. Pricing is fair and the developer experience is genuinely delightful.

Read full review →
GroqCAUTIOUS-BUY
The fastest inference you can buy

Groq's LPU inference delivers latency that no GPU-based competitor matches. But the model selection is limited and capacity constraints have been a real headache for production customers.

Read full review →

What changed at each vendor

Modal

No recent vendor changes tracked.

Groq
Nvidia unveils Groq 3 LPX inference accelerator at GTC 2026
Mar 19, 2026·feature add·source ↗

Side-by-Side Comparison

Objective metrics, no spin.

N/A
Rating
N/A
free✓ Better
Pricing tier
starter
medium
Learning curve
✓ Bettereasy
1–3 days
Setup time
Under 1 hour (OpenAI-compatible API)
3 listed
Integrations
3 listed
small, medium, large
Best company size
small, medium, large, enterprise
Top Features
Python-native (decorate to deploy)
Sub-second GPU cold starts
Serverless scaling to zero
Scheduled jobs and webhooks
Features
Top Features
LPU hardware (5–10x faster than GPUs)
OpenAI-compatible API
Hosts LLaMA, Mixtral, Gemma, Whisper
Sub-second 70B model responses
Choose Modal if...

Engineering teams deploying ML inference, batch ETL, or AI pipelines without wanting to manage GPU infrastructure. Developer experience is the best in the category.

Avoid Modal if...

Applications with sustained 24/7 GPU utilization — dedicated cloud GPU instances (Lambda Labs, Coreweave) are cheaper at scale.

Choose Groq if...

Any latency-sensitive AI application: voice agents, real-time chat, interactive assistants. Groq changes what feels possible on open-weights models.

Avoid Groq if...

Teams needing frontier closed models (Claude, GPT-4o) — Groq only serves open-weights. Also limited model selection vs. Together or Fireworks.

Both suited for: small, medium, large companies

Since both tools target small and medium and large companies, your decision should hinge on the specific use case above rather than company fit. Try the AI Advisor to get a recommendation tailored to your exact stack.

Still not sure? Describe your situation.

The AI advisor knows both tools and your full stack. Tell it your company size, current tools, and what's not working — it'll tell you which one actually fits.

Ask AI Advisor →

Other Cloud Infrastructure & DevOps Tools to Consider

If neither is the right fit, these are the next best alternatives in the same category.

Vercel

free

The frontend cloud — deploy, scale, and iterate on web applications instantly.

View profile →

Railway

starter

Modern cloud platform — deploy any stack in minutes without infrastructure expertise.

View profile →

Replicate

starter

Run open-source AI models via API — thousands of image, video, and audio models with one HTTP call.

View profile →
← Browse all tool comparisons