Skip to main content
← GPU inference hub

Inference comparison

Groq vs Modal

Managed inference API against serverless gpu. Editorial fit scores help shortlist; live pricing stays on the provider sites.

Editorial scores last reviewed August 7, 2026

Managed inference API

Groq

Token / request API pricing

vs

Serverless GPU

Modal

Serverless CPU/GPU time

Some outbound links use a first-party redirect hop for click counting. Commission is only claimed when a partner programme is active for that specific link — most vendor hops here are not paid placements. Affiliate disclosure.

Groq vs Modal GPU inference comparison
DimensionGroqModal
CategoryManaged inference APIServerless GPU
BillingToken / request API pricingServerless CPU/GPU time
GPU choiceFixed LPU-backed serving — no SKU selectionPlatform-managed GPU classes
Cold startTypically warm API endpointsCan be noticeable on cold containers
Model accessCurated high-speed model set on Groq CloudPackage models in images or pull at runtime
Best forLatency-sensitive chat, agents, and batch inference on Groq’s supported model setDevelopers who want GPU code as functions with autoscaling
Watch outModel catalog and deployment options are narrower than general GPU rental; verify your model is supported before committing architectureCold starts and platform abstractions matter more than picking a bare metal SKU
GPU choice (1–10)2/10Winner: 6/10
Time-to-serving (editorial) (1–10)Winner: 10/107/10
Price clarity (1–10)6/10Winner: 7/10
Production ops (1–10)8/108/10
Open-model breadth (1–10)6/10Winner: 7/10

Chart

Fit scores on the decision axes

Editorial 1–10 ratings for this pair only — not live pricing or latency benchmarks.

GPU choice

Pick exact GPUs

Time-to-serving (editorial)

Warm-path fit

Price clarity

Easy to forecast

Production ops

Less DIY ops

Open-model breadth

Catalog depth

Scores are editorial planning ratings (1–10) for product shape — not published $/hour quotes or vendor SLAs. Verify current pricing on each provider site.

How to decide

Prefer Groq when latency-sensitive chat, agents, and batch inference on groq’s supported model set. Prefer Modal when developers who want gpu code as functions with autoscaling. If those statements both feel true, rent a GPU for control and keep a managed API for peak traffic — do not force one product to do both jobs.

Common questions

Groq vs Modal

Answered from the verified figures on this page rather than general guidance.

How are Groq and Modal billed?

Groq uses token / request api pricing; Modal uses serverless cpu/gpu time. Marketplace hourly spend tracks GPU uptime; serverless and managed APIs bill for what you invoke — different failure modes if you forget to shut things down.

Which gives more control over the GPU, Groq or Modal?

Groq: Fixed LPU-backed serving — no SKU selection. Modal: Platform-managed GPU classes. Modal scores higher for GPU choice (6/10 vs 2/10). Pick a marketplace when you need a specific SKU; pick serverless or managed APIs when you want the platform to handle hardware.

Which has faster cold starts, Groq or Modal?

Groq: Typically warm API endpoints. Modal: Can be noticeable on cold containers. Our editorial ratings favour Groq for warm API speed (10/10 vs 7/10), but real latency depends on model size, region, and whether endpoints are kept warm. Those 1–10 scores are editorial rankings, not measured milliseconds — record your own TTFT/p95 on a warm endpoint in the target region before you buy on latency.

Should I use Groq or Modal?

Choose Groq when latency-sensitive chat, agents, and batch inference on groq’s supported model set. Choose Modal when developers who want gpu code as functions with autoscaling. Watch out: Model catalog and deployment options are narrower than general GPU rental; verify your model is supported before committing architecture Cold starts and platform abstractions matter more than picking a bare metal SKU

When should I use a managed API like Groq instead of renting a GPU?

Prefer a managed inference API when you want tokens quickly without CUDA ops and the model is already on the catalog. Prefer GPU rental when you need a specific SKU, custom serving stack, or sustained utilization that beats token pricing — size VRAM on /gpus first.